Search Results for author: Meng Wang

Found 281 papers, 105 papers with code

Large-Scale Few-Shot Learning via Multi-Modal Knowledge Discovery

no code implementations ECCV 2020 Shuo Wang, Jun Yue, Jianzhuang Liu, Qi Tian, Meng Wang

It is a challenging problem since (1) the identifying process is susceptible to over-fitting with limited samples of an object, and (2) the sample imbalance between a base (known knowledge) category and a novel category is easy to bias the recognition results.

Few-Shot Learning

Training A Small Emotional Vision Language Model for Visual Art Comprehension

no code implementations17 Mar 2024 Jing Zhang, Liang Zheng, Dan Guo, Meng Wang

This paper develops small vision language models to understand visual art, which, given an art work, aims to identify its emotion category and explain this prediction with natural language.

Zippo: Zipping Color and Transparency Distributions into a Single Diffusion Model

no code implementations17 Mar 2024 Kangyang Xie, BinBin Yang, Hao Chen, Meng Wang, Cheng Zou, Hui Xue, Ming Yang, Chunhua Shen

Beyond the superiority of the text-to-image diffusion model in generating high-quality images, recent studies have attempted to uncover its potential for adapting the learned semantic knowledge to visual perception tasks.

BlindDiff: Empowering Degradation Modelling in Diffusion Models for Blind Image Super-Resolution

1 code implementation15 Mar 2024 Feng Li, Yixuan Wu, Zichao Liang, Runmin Cong, Huihui Bai, Yao Zhao, Meng Wang

BlindDiff seamlessly integrates the MAP-based optimization into DMs, which constructs a joint distribution of the low-resolution (LR) observation, high-resolution (HR) data, and degradation kernels for the data and kernel priors, and solves the blind SR problem by unfolding MAP approach along with the reverse process.

Image Restoration Image Super-Resolution

Frequency Decoupling for Motion Magnification via Multi-Level Isomorphic Architecture

1 code implementation12 Mar 2024 Fei Wang, Dan Guo, Kun Li, Zhun Zhong, Meng Wang

To this end, we present FD4MM, a new paradigm of Frequency Decoupling for Motion Magnification with a Multi-level Isomorphic Architecture to capture multi-level high-frequency details and a stable low-frequency structure (motion field) in video space.

Motion Magnification Representation Learning

Benchmarking Micro-action Recognition: Dataset, Methods, and Applications

1 code implementation8 Mar 2024 Dan Guo, Kun Li, Bin Hu, Yan Zhang, Meng Wang

It offers insights into the feelings and intentions of individuals and is important for human-oriented applications such as emotion recognition and psychological assessment.

Action Recognition Benchmarking +1

Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis

1 code implementation27 Feb 2024 ZiCheng Zhang, Ruobing Zheng, Ziwen Liu, Congying Han, Tianqi Li, Meng Wang, Tiande Guo, Jingdong Chen, Bonan Li, Ming Yang

Recent works in implicit representations, such as Neural Radiance Fields (NeRF), have advanced the generation of realistic and animatable head avatars from video sequences.

Training Nonlinear Transformers for Efficient In-Context Learning: A Theoretical Learning and Generalization Analysis

no code implementations23 Feb 2024 Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

Despite the empirical success, the mechanics of how to train a Transformer to achieve ICL and the corresponding ICL capacity is mostly elusive due to the technical challenges of analyzing the nonconvex training problems resulting from the nonlinear self-attention and nonlinear activation in Transformers.

Binary Classification In-Context Learning

Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network

no code implementations18 Feb 2024 Lin Chen, Fengli Xu, Nian Li, Zhenyu Han, Meng Wang, Yong Li, Pan Hui

We propose a novel REasoning meta-STRUCTure search (ReStruct) framework that integrates LLM reasoning into the evolutionary procedure.

Language Modelling Large Language Model +1

Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering

no code implementations18 Feb 2024 Peijie Sun, Le Wu, Kun Zhang, Xiangzhi Chen, Meng Wang

Using the graph-based collaborative filtering model as our backbone and following the same data augmentation methods as the existing contrastive learning model SGL, we effectively enhance the performance of the recommendation model.

Collaborative Filtering Contrastive Learning +1

Training-free image style alignment for self-adapting domain shift on handheld ultrasound devices

no code implementations17 Feb 2024 Hongye Zeng, Ke Zou, Zhihao Chen, Yuchong Gao, Hongbo Chen, Haibin Zhang, Kang Zhou, Meng Wang, Rick Siow Mong Goh, Yong liu, Chang Jiang, Rui Zheng, Huazhu Fu

Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when directly applied to handheld device data.

Improving Cognitive Diagnosis Models with Adaptive Relational Graph Neural Networks

no code implementations15 Feb 2024 Pengyang Shao, Chen Gao, Lei Chen, Yonghui Yang, Kun Zhang, Meng Wang

Typically, these CD algorithms assist students by inferring their abilities (i. e., their proficiency levels on various knowledge concepts).

cognitive diagnosis

Beyond Imitation: Generating Human Mobility from Context-aware Reasoning with Large Language Models

no code implementations15 Feb 2024 Chenyang Shao, Fengli Xu, Bingbing Fan, Jingtao Ding, Yuan Yuan, Meng Wang, Yong Li

In this paper, we design a novel Mobility Generation as Reasoning (MobiGeaR) framework that prompts LLM to recursively generate mobility behaviour.

In-Context Learning

Revisiting the Power of Prompt for Visual Tuning

1 code implementation4 Feb 2024 Yuzhu Wang, Lechao Cheng, Chaowei Fang, Dingwen Zhang, Manni Duan, Meng Wang

Inspired by the observation that the prompt tokens tend to share high mutual information with patch tokens, we propose initializing prompts with downstream token prototypes.

Scalable Face Image Coding via StyleGAN Prior: Towards Compression for Human-Machine Collaborative Vision

no code implementations25 Dec 2023 Qi Mao, Chongyu Wang, Meng Wang, Shiqi Wang, Ruijie Chen, Libiao Jin, Siwei Ma

The accelerated proliferation of visual content and the rapid development of machine vision technologies bring significant challenges in delivering visual data on a gigantic scale, which shall be effectively represented to satisfy both human and machine requirements.

Image Compression

A Dual-way Enhanced Framework from Text Matching Point of View for Multimodal Entity Linking

1 code implementation19 Dec 2023 Shezheng Song, Shan Zhao, Chengyu Wang, Tianwei Yan, Shasha Li, Xiaoguang Mao, Meng Wang

Multimodal Entity Linking (MEL) aims at linking ambiguous mentions with multimodal information to entity in Knowledge Graph (KG) such as Wikipedia, which plays a key role in many applications.

Entity Linking Text Matching

Retrieval-Augmented Generation for Large Language Models: A Survey

1 code implementation18 Dec 2023 Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Qianyu Guo, Meng Wang, Haofen Wang

Large Language Models (LLMs) demonstrate significant capabilities but face challenges such as hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.

Hallucination Retrieval

EulerMormer: Robust Eulerian Motion Magnification via Dynamic Filtering within Transformer

1 code implementation7 Dec 2023 Fei Wang, Dan Guo, Kun Li, Meng Wang

Then, we introduce a novel dynamic filter that eliminates noise cues and preserves critical features in the motion magnification and amplification generation phases.

Denoising Motion Magnification

Sequencing-enabled Hierarchical Cooperative CAV On-ramp Merging Control with Enhanced Stability and Feasibility

no code implementations25 Nov 2023 Sixu Li, Yang Zhou, Xinyue Ye, Jiwan Jiang, Meng Wang

Subsequently, the lower-level control employs a longitudinal distributed model predictive control (MPC) supplemented by a virtual car-following (CF) concept to ensure asymptotic local stability, l_2 norm string stability, and safety.

Model Predictive Control

Continual Referring Expression Comprehension via Dual Modular Memorization

1 code implementation25 Nov 2023 Heng Tao Shen, Cheng Chen, Peng Wang, Lianli Gao, Meng Wang, Jingkuan Song

In this paper, we propose Continual Referring Expression Comprehension (CREC), a new setting for REC, where a model is learning on a stream of incoming tasks.

Memorization Referring Expression +1

Cut-and-Paste: Subject-Driven Video Editing with Attention Control

no code implementations20 Nov 2023 Zhichao Zuo, Zhao Zhang, Yan Luo, Yang Zhao, Haijun Zhang, Yi Yang, Meng Wang

This paper presents a novel framework termed Cut-and-Paste for real-word semantic video editing under the guidance of text prompt and additional reference image.

Object Video Editing

Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement

no code implementations20 Nov 2023 Yanyan Wei, Zhao Zhang, Jiahuan Ren, Xiaogang Xu, Richang Hong, Yi Yang, Shuicheng Yan, Meng Wang

The generalization capability of existing image restoration and enhancement (IRE) methods is constrained by the limited pre-trained datasets, making it difficult to handle agnostic inputs such as different degradation levels and scenarios beyond their design scopes.

Image Restoration Language Modelling

Mixed Attention Network for Cross-domain Sequential Recommendation

1 code implementation14 Nov 2023 GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang

Recent proposed cross-domain sequential recommendation models such as PiNet and DASL have a common drawback relying heavily on overlapped users in different domains, which limits their usage in practical recommender systems.

Sequential Recommendation

OR Residual Connection Achieving Comparable Accuracy to ADD Residual Connection in Deep Residual Spiking Neural Networks

1 code implementation11 Nov 2023 Yimeng Shan, Xuerui Qiu, Rui-Jie Zhu, Ruike Li, Meng Wang, Haicheng Qu

Spiking Neural Networks (SNNs) have garnered substantial attention in brain-like computing for their biological fidelity and the capacity to execute energy-efficient spike-driven operations.

Quantization

Unified Multi-modal Unsupervised Representation Learning for Skeleton-based Action Understanding

1 code implementation6 Nov 2023 Shengkai Sun, Daizong Liu, Jianfeng Dong, Xiaoye Qu, Junyu Gao, Xun Yang, Xun Wang, Meng Wang

In this manner, our framework is able to learn the unified representations of uni-modal or multi-modal skeleton input, which is flexible to different kinds of modality input for robust action understanding in practical cases.

Action Understanding Representation Learning +1

POS: A Prompts Optimization Suite for Augmenting Text-to-Video Generation

no code implementations2 Nov 2023 Shijie Ma, Huayi Xu, Mengjian Li, Weidong Geng, Meng Wang, Yaxiong Wang

This paper targets to enhance the diffusion-based text-to-video generation by improving the two input prompts, including the noise and the text.

Denoising POS +2

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $ε$-Greedy Exploration

no code implementations24 Oct 2023 Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury

This paper provides the first theoretical convergence and sample complexity analysis of the practical setting of DQNs with $\epsilon$-greedy policy.

Q-Learning

A Link Transmission Model with Variable Speed Limits and Turn-Level Queue Transmission at Signalized Intersections

no code implementations18 Oct 2023 Lei Wei, S. Travis Waller, Yu Mei, Yunpeng Wang, Meng Wang

The link transmission model (LTM) is an efficient and widely used macro-level approach for simulating traffic flow.

Exploring Sparse Spatial Relation in Graph Inference for Text-Based VQA

no code implementations13 Oct 2023 Sheng Zhou, Dan Guo, Jia Li, Xun Yang, Meng Wang

The associations between these repetitive objects are superfluous for answer reasoning; (2) two spatially distant OCR tokens detected in the image frequently have weak semantic dependencies for answer reasoning; and (3) the co-existence of nearby objects and tokens may be indicative of important visual cues for predicting answers.

Graph Learning Object +5

ASM: Adaptive Sample Mining for In-The-Wild Facial Expression Recognition

no code implementations9 Oct 2023 Ziyang Zhang, Xiao Sun, Liuwei An, Meng Wang

First, the Adaptive Threshold Learning module generates two thresholds, namely the clean and noisy thresholds, for each category.

Facial Expression Recognition Facial Expression Recognition (FER)

Dual-Path Temporal Map Optimization for Make-up Temporal Video Grounding

no code implementations12 Sep 2023 Jiaxiu Li, Kun Li, Jia Li, Guoliang Chen, Dan Guo, Meng Wang

Compared with the general video grounding task, MTVG focuses on meticulous actions and changes on the face.

Sentence text similarity +1

Dual Relation Alignment for Composed Image Retrieval

no code implementations5 Sep 2023 Xintong Jiang, Yaxiong Wang, Yujiao Wu, Meng Wang, Xueming Qian

Unlike the general image-text retrieval problem with only one alignment relation, i. e., image-text, we argue for the existence of two types of relations in composed image retrieval.

Image Retrieval Implicit Relations +3

Exploiting Diverse Feature for Multimodal Sentiment Analysis

no code implementations25 Aug 2023 Jia Li, Wei Qian, Kun Li, Qi Li, Dan Guo, Meng Wang

Specifically, we achieve the results of 0. 8492 and 0. 8439 for MuSe-Personalisation in terms of arousal and valence CCC.

Multimodal Sentiment Analysis

Fault Separation Based on An Excitation Operator with Application to a Quadrotor UAV

no code implementations20 Aug 2023 Sicheng Zhou, Meng Wang, Jindou Jia, Kexin Guo, Xiang Yu, Youmin Zhang, Lei Guo

This paper presents an excitation operator based fault separation architecture for a quadrotor unmanned aerial vehicle (UAV) subject to loss of effectiveness (LoE) faults, actuator aging, and load uncertainty.

Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph

no code implementations15 Aug 2023 Yi Liu, Hongrui Xuan, Bohan Li, Meng Wang, Tong Chen, Hongzhi Yin

However, the long-tail distribution of entities leads to sparsity in supervision signals, which weakens the quality of item representation when utilizing KG enhancement.

Collaborative Filtering Knowledge-Aware Recommendation +2

Dual-path TokenLearner for Remote Photoplethysmography-based Physiological Measurement with Facial Videos

1 code implementation15 Aug 2023 Wei Qian, Dan Guo, Kun Li, Xilan Tian, Meng Wang

Specifically, the proposed Dual-TL uses a Spatial TokenLearner (S-TL) to explore associations in different facial ROIs, which promises the rPPG prediction far away from noisy ROI disturbances.

ViGT: Proposal-free Video Grounding with Learnable Token in Transformer

no code implementations11 Aug 2023 Kun Li, Dan Guo, Meng Wang

First, we employed a sharing feature encoder to project both video and query into a joint feature space before performing cross-modal co-attention (i. e., video-to-query attention and query-to-video attention) to highlight discriminative features in each modality.

Feature Correlation regression +1

Data Augmentation for Human Behavior Analysis in Multi-Person Conversations

no code implementations3 Aug 2023 Kun Li, Dan Guo, Guoliang Chen, Feiyang Liu, Meng Wang

In this paper, we present the solution of our team HFUT-VUT for the MultiMediate Grand Challenge 2023 at ACM Multimedia 2023.

Joint Skeletal and Semantic Embedding Loss for Micro-gesture Classification

1 code implementation20 Jul 2023 Kun Li, Dan Guo, Guoliang Chen, Xinge Peng, Meng Wang

In this paper, we briefly introduce the solution of our team HFUT-VUT for the Micros-gesture Classification in the MiGA challenge at IJCAI 2023.

Action Classification Classification +2

Extreme Image Compression using Fine-tuned VQGANs

no code implementations17 Jul 2023 Qi Mao, Tinghan Yang, Yinuo Zhang, Zijian Wang, Meng Wang, Shiqi Wang, Siwei Ma

Remarkably, even with the loss of up to $20\%$ of indices, the images can be effectively restored with minimal perceptual loss.

Image Compression Quantization

A Multi-view Impartial Decision Network for Frontotemporal Dementia Diagnosis

no code implementations11 Jul 2023 Guoyao Deng, Ke Zou, Meng Wang, Xuedong Yuan, Sancong Ying, Huazhu Fu

To achieve this, we employ multiple expert models to extract evidence from the abundant neural network information contained in fMRI images.

Decision Making

Generative Contrastive Graph Learning for Recommendation

1 code implementation11 Jul 2023 Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang

Second, feature augmentation imposes the same scale noise augmentation on each node, which neglects the unique characteristics of nodes on the graph.

Collaborative Filtering Contrastive Learning +3

You Can Mask More For Extremely Low-Bitrate Image Compression

1 code implementation27 Jun 2023 Anqi Li, Feng Li, Jiaxin Han, Huihui Bai, Runmin Cong, Chunjie Zhang, Meng Wang, Weisi Lin, Yao Zhao

Extensive experiments have demonstrated that our approach outperforms recent state-of-the-art methods in R-D performance, visual quality, and downstream applications, at very low bitrates.

Image Compression

CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild

no code implementations26 Jun 2023 Li Ding, Jack Terwilliger, Aishni Parab, Meng Wang, Lex Fridman, Bruce Mehler, Bryan Reimer

Non-intrusive, real-time analysis of the dynamics of the eye region allows us to monitor humans' visual attention allocation and estimate their mental state during the performance of real-world tasks, which can potentially benefit a wide range of human-computer interaction (HCI) applications.

Blink estimation Keypoint Detection

Description-Enhanced Label Embedding Contrastive Learning for Text Classification

1 code implementation15 Jun 2023 Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang

Then, we propose a novel Relation of Relation Learning Network (R2-Net) for text classification, in which text classification and R2 classification are treated as optimization targets.

Contrastive Learning Relation +3

Exploring Resolution Fields for Scalable Image Compression with Uncertainty Guidance

1 code implementation15 Jun 2023 Dongyi Zhang, Feng Li, Man Liu, Runmin Cong, Huihui Bai, Meng Wang, Yao Zhao

In this work, we explore the potential of resolution fields in scalable image compression and propose the reciprocal pyramid network (RPN) that fulfills the need for more adaptable and versatile compression.

Image Compression

A Survey on Video Moment Localization

no code implementations13 Jun 2023 Meng Liu, Liqiang Nie, Yunxiao Wang, Meng Wang, Yong Rui

Video moment localization, also known as video moment retrieval, aiming to search a target segment within a video described by a given natural language query.

Moment Retrieval Retrieval +1

Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks

1 code implementation7 Jun 2023 Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen

In deep learning, mixture-of-experts (MoE) activates one or few experts (sub-networks) on a per-sample or per-token basis, resulting in significant computation reduction.

Unlearnable Examples Give a False Sense of Security: Piercing through Unexploitable Data with Learnable Examples

1 code implementation16 May 2023 Wan Jiang, Yunfeng Diao, He Wang, Jianxin Sun, Meng Wang, Richang Hong

Unfortunately, we find UEs provide a false sense of security, because they cannot stop unauthorized users from utilizing other unprotected data to remove the protection, by turning unlearnable data into learnable again.

SSD-MonoDETR: Supervised Scale-aware Deformable Transformer for Monocular 3D Object Detection

1 code implementation12 May 2023 Xuan He, Fan Yang, Kailun Yang, Jiacheng Lin, Haolong Fu, Meng Wang, Jin Yuan, Zhiyong Li

To tackle this problem, this paper proposes a novel "Supervised Scale-aware Deformable Attention" (SSDA) for monocular 3D object detection.

Monocular 3D Object Detection Object +1

Geometric Prior Based Deep Human Point Cloud Geometry Compression

no code implementations2 May 2023 Xinju Wu, Pingping Zhang, Meng Wang, Peilin Chen, Shiqi Wang, Sam Kwong

The emergence of digital avatars has raised an exponential increase in the demand for human point clouds with realistic and intricate details.

Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective Method

1 code implementation14 Apr 2023 Yixuan Li, Bolin Chen, Baoliang Chen, Meng Wang, Shiqi Wang, Weisi Lin

In this paper, we introduce the large-scale Compressed Face Video Quality Assessment (CFVQA) database, which is the first attempt to systematically understand the perceptual quality and diversified compression distortions in face videos.

Video Compression Video Quality Assessment +1

Identity-Guided Collaborative Learning for Cloth-Changing Person Reidentification

no code implementations10 Apr 2023 Zan Gao, Shenxun Wei, Weili Guan, Lei Zhu, Meng Wang, Shenyong Chen

Moreover, human semantic information and pedestrian identity information are not fully explored.

Federated Uncertainty-Aware Aggregation for Fundus Diabetic Retinopathy Staging

no code implementations23 Mar 2023 Meng Wang, Lianyu Wang, Xinxing Xu, Ke Zou, Yiming Qian, Rick Siow Mong Goh, Yong liu, Huazhu Fu

Our TWEU employs an evidential deep layer to produce the uncertainty score with the DR staging results for client reliability evaluation.

Federated Learning

Model Barrier: A Compact Un-Transferable Isolation Domain for Model Intellectual Property Protection

1 code implementation CVPR 2023 Lianyu Wang, Meng Wang, Daoqiang Zhang, Huazhu Fu

As scientific and technological advancements result from human intellectual labor and computational costs, protecting model intellectual property (IP) has become increasingly important to encourage model creators and owners.

Reliable Multimodality Eye Disease Screening via Mixture of Student's t Distributions

1 code implementation17 Mar 2023 Ke Zou, Tian Lin, Xuedong Yuan, Haoyu Chen, Xiaojing Shen, Meng Wang, Huazhu Fu

To address this issue, we introduce a novel multimodality evidential fusion pipeline for eye disease screening, EyeMoSt, which provides a measure of confidence for unimodality and elegantly integrates the multimodality information from a multi-distribution fusion perspective.

Decision Making

Facial Affect Recognition based on Transformer Encoder and Audiovisual Fusion for the ABAW5 Challenge

no code implementations16 Mar 2023 Ziyang Zhang, Liuwei An, Zishun Cui, Ao Xu, Tengteng Dong, Yueqi Jiang, Jingyi Shi, Xin Liu, Xiao Sun, Meng Wang

In this paper, we present our solutions for the 5th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW), which includes four sub-challenges of Valence-Arousal (VA) Estimation, Expression (Expr) Classification, Action Unit (AU) Detection and Emotional Reaction Intensity (ERI) Estimation.

Multimodal Feature Extraction and Fusion for Emotional Reaction Intensity Estimation and Expression Classification in Videos with Transformers

1 code implementation16 Mar 2023 Jia Li, Yin Chen, Xuesong Zhang, Jiantao Nie, Ziqiang Li, Yangchen Yu, Yan Zhang, Richang Hong, Meng Wang

In this paper, we present our advanced solutions to the two sub-challenges of Affective Behavior Analysis in the wild (ABAW) 2023: the Emotional Reaction Intensity (ERI) Estimation Challenge and Expression (Expr) Classification Challenge.

Classification

Adaptive Data-Free Quantization

1 code implementation CVPR 2023 Biao Qian, Yang Wang, Richang Hong, Meng Wang

Data-free quantization (DFQ) recovers the performance of quantized network (Q) without the original data, but generates the fake sample via a generator (G) by learning from full-precision network (P), which, however, is totally independent of Q, overlooking the adaptability of the knowledge from generated samples, i. e., informative or not to the learning process of Q, resulting into the overflow of generalization error.

Data Free Quantization

Improving Audio-Visual Video Parsing with Pseudo Visual Labels

no code implementations4 Mar 2023 Jinxing Zhou, Dan Guo, Yiran Zhong, Meng Wang

We perform extensive experiments on the LLP dataset and demonstrate that our method can generate high-quality segment-level pseudo labels with the help of our newly proposed loss and the label denoising strategy.

Denoising Pseudo Label

DC-Former: Diverse and Compact Transformer for Person Re-Identification

1 code implementation28 Feb 2023 Wen Li, Cheng Zou, Meng Wang, Furong Xu, Jianan Zhao, Ruobing Zheng, Yuan Cheng, Wei Chu

In this paper, we propose a Diverse and Compact Transformer (DC-Former) that can achieve a similar effect by splitting embedding space into multiple diverse and compact subspaces.

Person Re-Identification

Rethinking Data-Free Quantization as a Zero-Sum Game

1 code implementation19 Feb 2023 Biao Qian, Yang Wang, Richang Hong, Meng Wang

how to generate the samples with desirable adaptability to benefit the quantized network?

Data Free Quantization

A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity

no code implementations12 Feb 2023 Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen

Based on a data model characterizing both label-relevant and label-irrelevant tokens, this paper provides the first theoretical analysis of training a shallow ViT, i. e., one self-attention layer followed by a two-layer perceptron, for a classification task.

Information Theoretical Importance Sampling Clustering

no code implementations9 Feb 2023 Jiangshe Zhang, Lizhen Ji, Meng Wang

In this paper, we propose an information theoretical importance sampling based approach for clustering problems (ITISC) which minimizes the worst case of expected distortions under the constraint of distribution deviation.

Clustering Load Forecasting

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks

no code implementations6 Feb 2023 Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu

Due to the significant computational challenge of training large-scale graph neural networks (GNNs), various sparse learning techniques have been exploited to reduce memory and storage costs.

Sparse Learning

Reliable Federated Disentangling Network for Non-IID Domain Feature

no code implementations30 Jan 2023 Meng Wang, Kai Yu, Chun-Mei Feng, Yiming Qian, Ke Zou, Lianyu Wang, Rick Siow Mong Goh, Yong liu, Huazhu Fu

To the best of our knowledge, our proposed RFedDis is the first work to develop an FL approach based on evidential uncertainty combined with feature disentangling, which enhances the performance and reliability of FL in non-IID domain features.

Federated Learning

Audio-Visual Segmentation with Semantics

1 code implementation30 Jan 2023 Jinxing Zhou, Xuyang Shen, Jianyuan Wang, Jiayi Zhang, Weixuan Sun, Jing Zhang, Stan Birchfield, Dan Guo, Lingpeng Kong, Meng Wang, Yiran Zhong

To deal with these problems, we propose a new baseline method that uses a temporal pixel-wise audio-visual interaction module to inject audio semantics as guidance for the visual segmentation process.

Segmentation Semantic Segmentation +1

CSDR-BERT: a pre-trained scientific dataset match model for Chinese Scientific Dataset Retrieval

no code implementations30 Jan 2023 Xintao Chu, Jianping Liu, Jian Wang, XiaoFeng Wang, Yingfei Wang, Meng Wang, Xunxun Gu

As the number of open and shared scientific datasets on the Internet increases under the open science movement, efficiently retrieving these datasets is a crucial task in information retrieval (IR) research.

Information Retrieval Retrieval +2

FE-TCM: Filter-Enhanced Transformer Click Model for Web Search

no code implementations19 Jan 2023 Yingfei Wang, Jianping Liu, Jian Wang, XiaoFeng Wang, Meng Wang, Xintao Chu

In this paper, We use Transformer as the backbone network of feature extraction, add filter layer innovatively, and propose a new Filter-Enhanced Transformer Click Model (FE-TCM) for web search.

Face Inverse Rendering via Hierarchical Decoupling

1 code implementation17 Jan 2023 Meng Wang, Xiaojie Guo, Wenjing Dai, Jiawan Zhang

Previous face inverse rendering methods often require synthetic data with ground truth and/or professional equipment like a lighting stage.

Inverse Rendering

Nearest Neighbor-Based Contrastive Learning for Hyperspectral and LiDAR Data Classification

1 code implementation9 Jan 2023 Meng Wang, Feng Gao, Junyu Dong, Heng-Chao Li, Qian Du

It is commonly nontrivial to build a robust self-supervised learning model for multisource data classification, due to the fact that the semantic similarities of neighborhood regions are not exploited in existing contrastive learning framework.

Classification Contrastive Learning +2

Vocabulary-informed Zero-shot and Open-set Learning

1 code implementation3 Jan 2023 Yanwei Fu, Xiaomei Wang, Hanze Dong, Yu-Gang Jiang, Meng Wang, xiangyang xue, Leonid Sigal

Despite significant progress in object categorization, in recent years, a number of important challenges remain; mainly, the ability to learn from limited labeled data and to recognize object classes within large, potentially open, set of labels.

Object Categorization Open Set Learning +1

LP-DIF: Learning Local Pattern-Specific Deep Implicit Function for 3D Objects and Scenes

no code implementations CVPR 2023 Meng Wang, Yu-Shen Liu, Yue Gao, Kanle Shi, Yi Fang, Zhizhong Han

To capture geometry details, current mainstream methods divide 3D shapes into local regions and then learn each one with a local latent code via a decoder, where the decoder shares the geometric similarities among different local regions.

3D Reconstruction 3D Shape Representation

Domain Generalized Stereo Matching via Hierarchical Visual Transformation

no code implementations CVPR 2023 Tianyu Chang, Xun Yang, Tianzhu Zhang, Meng Wang

In this way, we can prevent the model from exploiting the artifacts of synthetic stereo images as shortcut features, thereby estimating the disparity maps more effectively based on the learned robust and shortcut-invariant representation.

Domain Generalization Stereo Matching

Reliable Joint Segmentation of Retinal Edema Lesions in OCT Images

1 code implementation1 Dec 2022 Meng Wang, Kai Yu, Chun-Mei Feng, Ke Zou, Yanyu Xu, Qingquan Meng, Rick Siow Mong Goh, Yong liu, Huazhu Fu

Specifically, aiming at improving the model's ability to learn the complex pathological features of retinal edema lesions in OCT images, we develop a novel segmentation backbone that integrates a wavelet-enhanced feature extractor network and a multi-scale transformer module of our newly designed.

Segmentation

Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods

1 code implementation27 Nov 2022 Zhengjie Huang, Zhenguang Liu, Jianhai Chen, Qinming He, Shuang Wu, Lei Zhu, Meng Wang

Meanwhile, decentralized applications have also attracted intense attention from the online gambling community, with more and more decentralized gambling platforms created through the help of smart contracts.

Retrieval

Contrastive Positive Sample Propagation along the Audio-Visual Event Line

1 code implementation18 Nov 2022 Jinxing Zhou, Dan Guo, Meng Wang

Visual and audio signals often coexist in natural environments, forming audio-visual events (AVEs).

Contrastive Learning Representation Learning

Long-Range Zero-Shot Generative Deep Network Quantization

no code implementations13 Nov 2022 Yan Luo, Yangcheng Gao, Zhao Zhang, Haijun Zhang, Mingliang Xu, Meng Wang

We find it is because: 1) a normal generator is hard to obtain high diversity of synthetic data, since it lacks long-range information to allocate attention to global features; 2) the synthetic images aim to simulate the statistics of real data, which leads to weak intra-class heterogeneity and limited feature richness.

Knowledge Distillation Quantization

OSIC: A New One-Stage Image Captioner Coined

no code implementations4 Nov 2022 Bo wang, Zhao Zhang, Mingbo Zhao, Xiaojie Jin, Mingliang Xu, Meng Wang

To obtain rich features, we use the Swin Transformer to calculate multi-level features, and then feed them into a novel dynamic multi-sight embedding module to exploit both global structure and local texture of input images.

Descriptive Language Modelling +2

A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems

no code implementations13 Oct 2022 Ehsan Hallaji, Roozbeh Razavi-Far, Meng Wang, Mehrdad Saif, Bruce Fardanesh

Using this information, the signal retrieval module can easily recover the original control signal and remove the injected false data.

Retrieval

Hybrid Multimodal Fusion for Humor Detection

no code implementations24 Sep 2022 Haojie Xu, Weifeng Liu, Jingwei Liu, Mingzheng Li, Yu Feng, Yasi Peng, Yunwei Shi, Xiao Sun, Meng Wang

Our experiments demonstrate the effectiveness of our proposed model and hybrid fusion strategy on multimodal fusion, and the AUC of our proposed model on the test set is 0. 8972.

Humor Detection

Delving Globally into Texture and Structure for Image Inpainting

1 code implementation17 Sep 2022 Haipeng Liu, Yang Wang, Meng Wang, Yong Rui

Our model is orthogonal to the fashionable arts, such as Convolutional Neural Networks (CNNs), Attention and Transformer model, from the perspective of texture and structure information for image inpainting.

Image Inpainting

Switchable Online Knowledge Distillation

1 code implementation12 Sep 2022 Biao Qian, Yang Wang, Hongzhi Yin, Richang Hong, Meng Wang

Instead of focusing on the accuracy gap at test phase by the existing arts, the core idea of SwitOKD is to adaptively calibrate the gap at training phase, namely distillation gap, via a switching strategy between two modes -- expert mode (pause the teacher while keep the student learning) and learning mode (restart the teacher).

Knowledge Distillation

Unsupervised Domain Adaptation via Style-Aware Self-intermediate Domain

no code implementations5 Sep 2022 Lianyu Wang, Meng Wang, Daoqiang Zhang, Huazhu Fu

Specifically, we propose a novel learning strategy of SSID, which selects samples from both source and target domains as anchors, and then randomly fuses the object and style features of these anchors to generate labeled and style-rich intermediate auxiliary features for knowledge transfer.

Transfer Learning Unsupervised Domain Adaptation

Multi-modal Contrastive Representation Learning for Entity Alignment

1 code implementation COLING 2022 Zhenxi Lin, Ziheng Zhang, Meng Wang, Yinghui Shi, Xian Wu, Yefeng Zheng

Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs, which consist of structural triples and images associated with entities.

Ranked #2 on Multi-modal Entity Alignment on UMVM-oea-d-w-v1 (using extra training data)

Contrastive Learning Knowledge Graphs +2

Temporal Action Localization with Multi-temporal Scales

no code implementations16 Aug 2022 Zan Gao, Xinglei Cui, Tao Zhuo, Zhiyong Cheng, An-An Liu, Meng Wang, Shenyong Chen

However, the temporal features of a low-level scale lack enough semantics for action classification while a high-level scale cannot provide rich details of the action boundaries.

Action Classification Avg +1

TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning

no code implementations6 Aug 2022 Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li

In conclusion, TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines.

Transfer Learning

Deep Uncalibrated Photometric Stereo via Inter-Intra Image Feature Fusion

no code implementations6 Aug 2022 Fangzhou Gao, Meng Wang, Lianghao Zhang, Li Wang, Jiawan Zhang

This paper presents a new method for deep uncalibrated photometric stereo, which efficiently utilizes the inter-image representation to guide the normal estimation.

Inverse Rendering

Hybrid Multimodal Feature Extraction, Mining and Fusion for Sentiment Analysis

1 code implementation5 Aug 2022 Jia Li, Ziyang Zhang, Junjie Lang, Yueqi Jiang, Liuwei An, Peng Zou, Yangyang Xu, Sheng Gao, Jie Lin, Chunxiao Fan, Xiao Sun, Meng Wang

In this paper, we present our solutions for the Multimodal Sentiment Analysis Challenge (MuSe) 2022, which includes MuSe-Humor, MuSe-Reaction and MuSe-Stress Sub-challenges.

Data Augmentation Humor Detection +1

Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers

no code implementations22 Jul 2022 Jia Li, Jiantao Nie, Dan Guo, Richang Hong, Meng Wang

Here, we regard an expressive face as the comprehensive result of a set of facial muscle movements on one's poker face (i. e., emotionless face), inspired by Facial Action Coding System.

Disentanglement Facial Expression Recognition +1

A Semantic-aware Attention and Visual Shielding Network for Cloth-changing Person Re-identification

no code implementations18 Jul 2022 Zan Gao, Hongwei Wei, Weili Guan, Jie Nie, Meng Wang, Shenyong Chen

In addition, a visual clothes shielding module (VCS) is also designed to extract a more robust feature representation for the cloth-changing task by covering the clothing regions and focusing the model on the visual semantic information unrelated to the clothes.

Cloth-Changing Person Re-Identification Semantic Segmentation

A Synergistic Compilation Workflow for Tackling Crosstalk in Quantum Machines

no code implementations12 Jul 2022 Fei Hua, Yuwei Jin, Ang Li, Chenxu Liu, Meng Wang, Yanhao Chen, Chi Zhang, Ari Hayes, Samuel Stein, Minghao Guo, Yipeng Huang, Eddy Z. Zhang

Evaluations through simulation and on real IBM-Q devices show that our framework can significantly reduce the error rate by up to 6$\times$, with only $\sim$60\% circuit depth compared to state-of-the-art gate scheduling approaches.

Scheduling

Audio-Visual Segmentation

1 code implementation11 Jul 2022 Jinxing Zhou, Jianyuan Wang, Jiayi Zhang, Weixuan Sun, Jing Zhang, Stan Birchfield, Dan Guo, Lingpeng Kong, Meng Wang, Yiran Zhong

To deal with the AVS problem, we propose a novel method that uses a temporal pixel-wise audio-visual interaction module to inject audio semantics as guidance for the visual segmentation process.

Segmentation

Recent Results of Energy Disaggregation with Behind-the-Meter Solar Generation

no code implementations7 Jul 2022 Ming Yi, Meng Wang

Compared with deterministic dictionary learning, the Bayesian dictionary learning-based approach provides the uncertainty measure for the disaggregation results, at the cost of increased computational complexity.

Dictionary Learning

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

no code implementations7 Jul 2022 Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, JinJun Xiong

Graph convolutional networks (GCNs) have recently achieved great empirical success in learning graph-structured data.

Node Classification

Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data

no code implementations7 Jul 2022 Hongkang Li, Shuai Zhang, Meng Wang

In addition, for the first time, this paper characterizes the impact of the input distributions on the sample complexity and the learning rate.

Solutions for Fine-grained and Long-tailed Snake Species Recognition in SnakeCLEF 2022

no code implementations4 Jul 2022 Cheng Zou, Furong Xu, Meng Wang, Wen Li, Yuan Cheng

Automatic snake species recognition is important because it has vast potential to help lower deaths and disabilities caused by snakebites.

Self-Supervised Learning

KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D Correspondences

1 code implementation21 Jun 2022 Xuanhan Wang, Lianli Gao, Yixuan Zhou, Jingkuan Song, Meng Wang

Human densepose estimation, aiming at establishing dense correspondences between 2D pixels of human body and 3D human body template, is a key technique in enabling machines to have an understanding of people in images.

Human Part Segmentation Transfer Learning

TBraTS: Trusted Brain Tumor Segmentation

3 code implementations19 Jun 2022 Ke Zou, Xuedong Yuan, Xiaojing Shen, Meng Wang, Huazhu Fu

In our method, uncertainty is modeled explicitly using subjective logic theory, which treats the predictions of backbone neural network as subjective opinions by parameterizing the class probabilities of the segmentation as a Dirichlet distribution.

Brain Tumor Segmentation Segmentation +1

A Review-aware Graph Contrastive Learning Framework for Recommendation

1 code implementation26 Apr 2022 Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li

Second, while most current models suffer from limited user behaviors, can we exploit the unique self-supervised signals in the review-aware graph to guide two recommendation components better?

Contrastive Learning Recommendation Systems +1

Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy

no code implementations25 Apr 2022 Chengxin Chen, Meng Wang, Pengyuan Zhang

Recently, audio-visual scene classification (AVSC) has attracted increasing attention from multidisciplinary communities.

Scene Classification Transfer Learning

Detail-recovery Image Deraining via Dual Sample-augmented Contrastive Learning

1 code implementation6 Apr 2022 Yiyang Shen, Mingqiang Wei, Sen Deng, Wenhan Yang, Yongzhen Wang, Xiao-Ping Zhang, Meng Wang, Jing Qin

To bridge the two domain gaps, we propose a semi-supervised detail-recovery image deraining network (Semi-DRDNet) with dual sample-augmented contrastive learning.

Contrastive Learning Rain Removal

Thinking inside The Box: Learning Hypercube Representations for Group Recommendation

1 code implementation6 Apr 2022 Tong Chen, Hongzhi Yin, Jing Long, Quoc Viet Hung Nguyen, Yang Wang, Meng Wang

Such user and group preferences are commonly represented as points in the vector space (i. e., embeddings), where multiple user embeddings are compressed into one to facilitate ranking for group-item pairs.

Decision Making

Multi-modal Emotion Estimation for in-the-wild Videos

no code implementations24 Mar 2022 Liyu Meng, Yuchen Liu, Xiaolong Liu, Zhaopei Huang, Yuan Cheng, Meng Wang, Chuanhe Liu, Qin Jin

In this paper, we briefly introduce our submission to the Valence-Arousal Estimation Challenge of the 3rd Affective Behavior Analysis in-the-wild (ABAW) competition.

Arousal Estimation

How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis

no code implementations21 Jan 2022 Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, JinJun Xiong

Self-training, a semi-supervised learning algorithm, leverages a large amount of unlabeled data to improve learning when the labeled data are limited.

Compact Bidirectional Transformer for Image Captioning

1 code implementation6 Jan 2022 Yuanen Zhou, Zhenzhen Hu, Daqing Liu, Huixia Ben, Meng Wang

In this paper, we introduce a Compact Bidirectional Transformer model for image captioning that can leverage bidirectional context implicitly and explicitly while the decoder can be executed parallelly.

Image Captioning Sentence

TextRGNN: Residual Graph Neural Networks for Text Classification

no code implementations30 Dec 2021 Jiayuan Chen, Boyu Zhang, Yinfei Xu, Meng Wang

Recently, text classification model based on graph neural network (GNN) has attracted more and more attention.

Language Modelling text-classification +1

HBReID: Harder Batch for Re-identification

no code implementations9 Dec 2021 Wen Li, Furong Xu, Jianan Zhao, Ruobing Zheng, Cheng Zou, Meng Wang, Yuan Cheng

Triplet loss is a widely adopted loss function in ReID task which pulls the hardest positive pairs close and pushes the hardest negative pairs far away.

Person Re-Identification

Uncovering the Local Hidden Community Structure in Social Networks

no code implementations8 Dec 2021 Meng Wang, Boyu Li, Kun He, John E. Hopcroft

We theoretically show that our method can avoid some situations that a broken community and the local community are regarded as one community in the subgraph, leading to the inaccuracy on detection which can be caused by global hidden community detection methods.

Local Community Detection

Decoupled Low-light Image Enhancement

1 code implementation29 Nov 2021 Shijie Hao, Xu Han, Yanrong Guo, Meng Wang

On the other hand, since the parameter matrix learned from the first stage is aware of the lightness distribution and the scene structure, it can be incorporated into the second stage as the complementary information.

Low-Light Image Enhancement

Learning Non-Stationary Time-Series with Dynamic Pattern Extractions

no code implementations20 Nov 2021 Xipei Wang, Haoyu Zhang, Yuanbo Zhang, Meng Wang, Jiarui Song, Tin Lai, Matloob Khushi

Our results show that our model can predict 4-hour future trends with high accuracy in the Forex dataset, which is crucial in realistic scenarios to assist foreign exchange trading decision making.

Decision Making Dynamic Time Warping +2

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks

no code implementations12 Oct 2021 Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, JinJun Xiong

Moreover, when the algorithm for training a pruned neural network is specified as an (accelerated) stochastic gradient descent algorithm, we theoretically show that the number of samples required for achieving zero generalization error is proportional to the number of the non-pruned weights in the hidden layer.

Vibration-based Uncertainty Estimation for Learning from Limited Supervision

no code implementations29 Sep 2021 Hengtong Hu, Lingxi Xie, Yinquan Wang, Richang Hong, Meng Wang, Qi Tian

We investigate the problem of estimating uncertainty for training data, so that deep neural networks can make use of the results for learning from limited supervision.

Active Learning

How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis

no code implementations ICLR 2022 Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, JinJun Xiong

Self-training, a semi-supervised learning algorithm, leverages a large amount of unlabeled data to improve learning when the labeled data are limited.

Learning the Representation of Behavior Styles with Imitation Learning

no code implementations29 Sep 2021 Xiao Liu, Meng Wang, Zhaorong Wang, Yingfeng Chen, Yujing Hu, Changjie Fan, Chongjie Zhang

Imitation learning is one of the methods for reproducing expert demonstrations adaptively by learning a mapping between observations and actions.

Imitation Learning

Multi View Spatial-Temporal Model for Travel Time Estimation

1 code implementation15 Sep 2021 Zichuan Liu, Zhaoyang Wu, Meng Wang, Rui Zhang

Specifically, we use graph2vec to model the spatial view, dual-channel temporal module to model the trajectory view, and structural embedding to model traffic semantics.

Travel Time Estimation

Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning

1 code implementation12 Sep 2021 Yongrui Chen, Xinnan Guo, Chaojie Wang, Jian Qiu, Guilin Qi, Meng Wang, Huiying Li

Compared to the larger pre-trained model and the tabular-specific pre-trained model, our approach is still competitive.

Meta-Learning Text-To-SQL

ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration

1 code implementation16 Aug 2021 Yuhao Cui, Zhou Yu, Chunqi Wang, Zhongzhou Zhao, Ji Zhang, Meng Wang, Jun Yu

Nevertheless, most existing VLP approaches have not fully utilized the intrinsic knowledge within the image-text pairs, which limits the effectiveness of the learned alignments and further restricts the performance of their models.

Visual Reasoning

Multigranular Visual-Semantic Embedding for Cloth-Changing Person Re-identification

no code implementations10 Aug 2021 Zan Gao, Hongwei Wei, Weili Guan, Weizhi Nie, Meng Liu, Meng Wang

To solve these issues, in this work, a novel multigranular visual-semantic embedding algorithm (MVSE) is proposed for cloth-changing person ReID, where visual semantic information and human attributes are embedded into the network, and the generalized features of human appearance can be well learned to effectively solve the problem of clothing changes.

Cloth-Changing Person Re-Identification

TBNet:Two-Stream Boundary-aware Network for Generic Image Manipulation Localization

no code implementations10 Aug 2021 Zan Gao, Chao Sun, Zhiyong Cheng, Weili Guan, AnAn Liu, Meng Wang

In this work, a novel end-to-end two-stream boundary-aware network (abbreviated as TBNet) is proposed for generic image manipulation localization in which the RGB stream, the frequency stream, and the boundary artifact location are explored in a unified framework.

Image Manipulation Image Manipulation Localization

LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matching

no code implementations6 Aug 2021 Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, Meng Wang

In order to overcome this problem and boost the performance of attention mechanism, we propose a novel dynamic re-read attention, which can pay close attention to one small region of sentences at each step and re-read the important parts for better sentence representations.

Language Modelling Natural Language Inference +2

Few-shot Learning with Global Relatedness Decoupled-Distillation

no code implementations12 Jul 2021 Yuan Zhou, Yanrong Guo, Shijie Hao, Richang Hong, ZhengJun Zha, Meng Wang

To overcome these problems, we propose a new Global Relatedness Decoupled-Distillation (GRDD) method using the global category knowledge and the Relatedness Decoupled-Distillation (RDD) strategy.

Few-Shot Learning Metric Learning

Discrimination-Aware Mechanism for Fine-Grained Representation Learning

no code implementations CVPR 2021 Furong Xu, Meng Wang, Wei zhang, Yuan Cheng, Wei Chu

Therefore, there is a need for a training mechanism that enforces the discriminativeness of all the elements in the feature to capture more the subtle visual cues.

Representation Learning Retrieval

Single View Physical Distance Estimation using Human Pose

no code implementations ICCV 2021 Xiaohan Fei, Henry Wang, Xiangyu Zeng, Lin Lee Cheong, Meng Wang, Joseph Tighe

We propose a fully automated system that simultaneously estimates the camera intrinsics, the ground plane, and physical distances between people from a single RGB image or video captured by a camera viewing a 3-D scene from a fixed vantage point.

Camera Calibration

Semi-Autoregressive Transformer for Image Captioning

1 code implementation17 Jun 2021 Yuanen Zhou, Yong Zhang, Zhenzhen Hu, Meng Wang

To tackle this issue, non-autoregressive image captioning models have recently been proposed to significantly accelerate the speed of inference by generating all words in parallel.

Image Captioning

DGA-Net Dynamic Gaussian Attention Network for Sentence Semantic Matching

no code implementations9 Jun 2021 Kun Zhang, Guangyi Lv, Meng Wang, Enhong Chen

Then, we develop a Dynamic Gaussian Attention (DGA) to dynamically capture the important parts and corresponding local contexts from a detailed perspective.

Language Modelling Relation +2

Harnessing Unrecognizable Faces for Improving Face Recognition

no code implementations8 Jun 2021 Siqi Deng, Yuanjun Xiong, Meng Wang, Wei Xia, Stefano Soatto

The common implementation of face recognition systems as a cascade of a detection stage and a recognition or verification stage can cause problems beyond failures of the detector.

Face Recognition Quantization

Learning Elastic Embeddings for Customizing On-Device Recommenders

no code implementations4 Jun 2021 Tong Chen, Hongzhi Yin, Yujia Zheng, Zi Huang, Yang Wang, Meng Wang

The core idea is to compose elastic embeddings for each item, where an elastic embedding is the concatenation of a set of embedding blocks that are carefully chosen by an automated search function.

Recommendation Systems

Deconfounded Video Moment Retrieval with Causal Intervention

1 code implementation3 Jun 2021 Xun Yang, Fuli Feng, Wei Ji, Meng Wang, Tat-Seng Chua

To fill the research gap, we propose a causality-inspired VMR framework that builds structural causal model to capture the true effect of query and video content on the prediction.

Moment Retrieval Retrieval

Privileged Graph Distillation for Cold Start Recommendation

no code implementations31 May 2021 Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang

The teacher model is composed of a heterogeneous graph structure for warm users and items with privileged CF links.

Attribute Collaborative Filtering +1

Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation

1 code implementation16 May 2021 Lei Chen, Le Wu, Kun Zhang, Richang Hong, Meng Wang

Despite the performance gain of these implicit feedback based models, the recommendation results are still far from satisfactory due to the sparsity of the observed item set for each user.

Collaborative Filtering

A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation

1 code implementation27 Apr 2021 Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang

Influenced by the great success of deep learning in computer vision and language understanding, research in recommendation has shifted to inventing new recommender models based on neural networks.

Collaborative Filtering Sequential Recommendation

Quaternion Factorization Machines: A Lightweight Solution to Intricate Feature Interaction Modelling

no code implementations5 Apr 2021 Tong Chen, Hongzhi Yin, Xiangliang Zhang, Zi Huang, Yang Wang, Meng Wang

As a well-established approach, factorization machine (FM) is capable of automatically learning high-order interactions among features to make predictions without the need for manual feature engineering.

Feature Engineering

Positive Sample Propagation along the Audio-Visual Event Line

2 code implementations CVPR 2021 Jinxing Zhou, Liang Zheng, Yiran Zhong, Shijie Hao, Meng Wang

To encourage the network to extract high correlated features for positive samples, a new audio-visual pair similarity loss is proposed.

audio-visual event localization

Connected and Automated Vehicle Distributed Control for On-ramp Merging Scenario: A Virtual Rotation Approach

no code implementations28 Mar 2021 Tianyi Chen, Meng Wang, Siyuan Gong, Yang Zhou, Bin Ran

In this study, we propose a rotation-based connected automated vehicle (CAV) distributed cooperative control strategy for an on-ramp merging scenario.

Flatband-Induced Itinerant Ferromagnetism in RbCo$_2$Se$_2$

no code implementations11 Mar 2021 Jianwei Huang, Zhicai Wang, Hongsheng Pang, Han Wu, Huibo Cao, Sung-Kwan Mo, Avinash Rustagi, A. F. Kemper, Meng Wang, Ming Yi, R. J. Birgeneau

$A$Co$_2$Se$_2$ ($A$=K, Rb, Cs) is a homologue of the iron-based superconductor, $A$Fe$_2$Se$_2$.

Superconductivity Materials Science

Spectral Top-Down Recovery of Latent Tree Models

1 code implementation26 Feb 2021 Yariv Aizenbud, Ariel Jaffe, Meng Wang, Amber Hu, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger

For large trees, a common approach, termed divide-and-conquer, is to recover the tree structure in two steps.

Measurement of the absolute branching fractions for purely leptonic $D_s^+$ decays

no code implementations23 Feb 2021 BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei LI, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, H. F. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, A. Q. Zhang, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

Constraining our measurement to the Standard Model expectation of lepton universality ($R=9. 75$), we find the more precise results $\cal B(D_s^+\to \tau^+\nu_\tau) = (5. 22\pm0. 10\pm 0. 14)\times10^{-2}$ and $A_{\it CP}(\tau^\pm\nu_\tau) = (-0. 1\pm1. 9\pm1. 0)\%$.

High Energy Physics - Experiment

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

1 code implementation ICLR 2021 Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang

Despite the generalization power of the meta-model, it remains elusive that how adversarial robustness can be maintained by MAML in few-shot learning.

Adversarial Attack Adversarial Robustness +3

Learning Fair Representations for Recommendation: A Graph-based Perspective

1 code implementation18 Feb 2021 Le Wu, Lei Chen, Pengyang Shao, Richang Hong, Xiting Wang, Meng Wang

For each user, this transformation is achieved under the adversarial learning of a user-centric graph, in order to obfuscate each sensitive feature between both the filtered user embedding and the sub graph structures of this user.

Fairness Recommendation Systems

Cross section measurement of $e^+e^- \to p\bar{p}η$ and $e^+e^- \to p\bar{p}ω$ at center-of-mass energies between 3.773 GeV and 4.6 GeV

no code implementations8 Feb 2021 M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N. Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, Ke Li, L. K. Li, Lei LI, P. L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. Liu, M. H. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, W. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, Lei Zhang, S. Zhang, S. F. Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

Based on $14. 7~\textrm{fb}^{-1}$ of $e^+e^-$ annihilation data collected with the BESIII detector at the BEPCII collider at 17 different center-of-mass energies between $3. 7730~\textrm{GeV}$ and $4. 5995~\textrm{GeV}$, Born cross sections of the two processes $e^+e^- \to p\bar{p}\eta$ and $e^+e^- \to p\bar{p}\omega$ are measured for the first time.

High Energy Physics - Experiment

Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer

2 code implementations26 Jan 2021 Liang Lin, Yiming Gao, Ke Gong, Meng Wang, Xiaodan Liang

Prior highly-tuned image parsing models are usually studied in a certain domain with a specific set of semantic labels and can hardly be adapted into other scenarios (e. g., sharing discrepant label granularity) without extensive re-training.

Graph Representation Learning Human Parsing +2

Learning One-hidden-layer Neural Networks on Gaussian Mixture Models with Guaranteed Generalizability

no code implementations1 Jan 2021 Hongkang Li, Shuai Zhang, Meng Wang

Instead of following the conventional and restrictive assumption in the literature that the input features follow the standard Gaussian distribution, this paper, for the first time, analyzes a more general and practical scenario that the input features follow a Gaussian mixture model of a finite number of Gaussian distributions of various mean and variance.

Binary Classification

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks

no code implementations NeurIPS 2021 Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, JinJun Xiong

Moreover, as the algorithm for training a sparse neural network is specified as (accelerated) stochastic gradient descent algorithm, we theoretically show that the number of samples required for achieving zero generalization error is proportional to the number of the non-pruned model weights in the hidden layer.

Motion Prediction Using Trajectory Cues

1 code implementation ICCV 2021 Zhenguang Liu, Pengxiang Su, Shuang Wu, Xuanjing Shen, Haipeng Chen, Yanbin Hao, Meng Wang

Predicting human motion from a historical pose sequence is at the core of many applications in computer vision.

motion prediction

Measurements of the center-of-mass energies of $e^{+}e^{-}$ collisions at BESIII

no code implementations29 Dec 2020 BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, N Hüsken, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei LI, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

During the 2016-17 and 2018-19 running periods, the BESIII experiment collected 7. 5~fb$^{-1}$ of $e^+e^-$ collision data at center-of-mass energies ranging from 4. 13 to 4. 44 GeV.

High Energy Physics - Experiment

R$^2$-Net: Relation of Relation Learning Network for Sentence Semantic Matching

no code implementations16 Dec 2020 Kun Zhang, Le Wu, Guangyi Lv, Meng Wang, Enhong Chen, Shulan Ruan

Sentence semantic matching is one of the fundamental tasks in natural language processing, which requires an agent to determine the semantic relation among input sentences.

Relation Relation Classification +1

Search for the reaction $e^{+}e^{-} \rightarrow π^{+}π^{-} χ_{cJ}$ and a charmonium-like structure decaying to $χ_{cJ}π^{\pm}$ between 4.18 and 4.60 GeV

no code implementations4 Dec 2020 BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, A. Amoroso, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Fu, X. L. Gao, Y. Gao, Y. G. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, S. Han, T. T. Han, T. Z. Han, X. Q. Hao, F. A. Harris, N. Hüsken, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, Ke Li, L. K. Li, Lei LI, P. L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, D. Y. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, Y. F. Long, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. N. Ma, X. X. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, D. C. Shan, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, Q. Q. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, V. Thoren, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Y. J. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, X. A. Xiong, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, R. X. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, W. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, Lei Zhang, S. Zhang, S. F. Zhang, T. J. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

We search for the process $e^{+}e^{-}\rightarrow \pi ^{+}\pi ^{-} \chi_{cJ}$ ($J=0, 1, 2$) and for a charged charmonium-like state in the $\pi ^{\pm} \chi_{cJ}$ subsystem.

High Energy Physics - Experiment

Positive-Congruent Training: Towards Regression-Free Model Updates

no code implementations CVPR 2021 Sijie Yan, Yuanjun Xiong, Kaustav Kundu, Shuo Yang, Siqi Deng, Meng Wang, Wei Xia, Stefano Soatto

Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error.

Image Classification regression

LIAF-Net: Leaky Integrate and Analog Fire Network for Lightweight and Efficient Spatiotemporal Information Processing

no code implementations12 Nov 2020 Zhenzhi Wu, Hehui Zhang, Yihan Lin, Guoqi Li, Meng Wang, Ye Tang

To address this issue, in this work, we propose a Leaky Integrate and Analog Fire (LIAF) neuron model, so that analog values can be transmitted among neurons, and a deep network termed as LIAF-Net is built on it for efficient spatiotemporal processing.

Question Answering

Online Action Detection in Streaming Videos with Time Buffers

no code implementations6 Oct 2020 BoWen Zhang, Hao Chen, Meng Wang, Yuanjun Xiong

We formulate the problem of online temporal action detection in live streaming videos, acknowledging one important property of live streaming videos that there is normally a broadcast delay between the latest captured frame and the actual frame viewed by the audience.

Online Action Detection

Revealing Secrets in SPARQL Session Level

1 code implementation13 Sep 2020 Xinyue Zhang, Meng Wang, Muhammad Saleem, Axel-Cyrille Ngonga Ngomo, Guilin Qi, Haofen Wang

Based on Semantic Web technologies, knowledge graphs help users to discover information of interest by using live SPARQL services.

Knowledge Graphs

Dual Encoding for Video Retrieval by Text

1 code implementation10 Sep 2020 Jianfeng Dong, Xirong Li, Chaoxi Xu, Xun Yang, Gang Yang, Xun Wang, Meng Wang

In this paper we achieve this by proposing a dual deep encoding network that encodes videos and queries into powerful dense representations of their own.

Ranked #3 on Ad-hoc video search on TRECVID-AVS16 (IACC.3) (using extra training data)

Ad-hoc video search Retrieval +2

Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior

no code implementations8 Sep 2020 Yan Zhang, Zhao Zhang, Yang Wang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang

Nonnegative matrix factorization is usually powerful for learning the "shallow" parts-based representation, but it clearly fails to discover deep hierarchical information within both the basis and representation spaces.

Clustering Graph Learning +1

A Survey on Large-scale Machine Learning

1 code implementation10 Aug 2020 Meng Wang, Weijie Fu, Xiangnan He, Shijie Hao, Xindong Wu

Machine learning can provide deep insights into data, allowing machines to make high-quality predictions and having been widely used in real-world applications, such as text mining, visual classification, and recommender systems.

BIG-bench Machine Learning Computational Efficiency +1

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

1 code implementation ECCV 2020 Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, JinJun Xiong, Meng Wang

When the training data are maliciously tampered, the predictions of the acquired deep neural network (DNN) can be manipulated by an adversary known as the Trojan attack (or poisoning backdoor attack).

Backdoor Attack

Feature Pyramid Transformer

1 code implementation ECCV 2020 Dong Zhang, Hanwang Zhang, Jinhui Tang, Meng Wang, Xiansheng Hua, Qianru Sun

Yet, the non-local spatial interactions are not across scales, and thus they fail to capture the non-local contexts of objects (or parts) residing in different scales.

Instance Segmentation object-detection +3

Learning to Discretely Compose Reasoning Module Networks for Video Captioning

1 code implementation17 Jul 2020 Ganchao Tan, Daqing Liu, Meng Wang, Zheng-Jun Zha

However, existing visual reasoning methods designed for visual question answering are not appropriate to video captioning, for it requires more complex visual reasoning on videos over both space and time, and dynamic module composition along the generation process.

Question Answering Sentence +3

Model independent determination of the spin of the $Ω^{-}$ and its polarization alignment in $ψ(3686)\rightarrowΩ^{-}\barΩ^{+}$

no code implementations7 Jul 2020 M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, A. Amoroso, Q. An, Anita, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. B. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Fu, X. L. Gao, Y. Gao, Y. G. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, S. Han, T. T. Han, T. Z. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, N. Huesken, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, L. Lavezzi, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, Ke Li, L. K. Li, Lei LI, P. L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, L. Z. Liao, J. Libby, C. X. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, D. Y. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, Y. F. Long, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. N. Ma, X. X. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. -B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, D. C. Shan, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, Q. Q. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, V. Thoren, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Y. J. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, X. A. Xiong, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, R. X. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, W. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, T. J. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, X. L. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

We present an analysis of the process $\psi(3686) \to \Omega^- \bar{\Omega}^+$ ($\Omega^-\to K^-\Lambda$, $\bar{\Omega}^+\to K^+\bar{\Lambda}$, $\Lambda\to p\pi^-$, $\bar{\Lambda}\to \bar{p}\pi^+$) based on a data set of $448\times 10^6$ $\psi(3686)$ decays collected with the BESIII detector at the BEPCII electron-positron collider.

High Energy Physics - Experiment

Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval

no code implementations6 Jul 2020 Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, Tat-Seng Chua

To facilitate video retrieval with complex queries, we propose a Tree-augmented Cross-modal Encoding method by jointly learning the linguistic structure of queries and the temporal representation of videos.

Retrieval Video Retrieval

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

no code implementations ICML 2020 Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, JinJun Xiong

In this paper, we provide a theoretically-grounded generalizability analysis of GNNs with one hidden layer for both regression and binary classification problems.

Binary Classification General Classification +1

Recurrent Relational Memory Network for Unsupervised Image Captioning

no code implementations24 Jun 2020 Dan Guo, Yang Wang, Peipei Song, Meng Wang

Unsupervised image captioning with no annotations is an emerging challenge in computer vision, where the existing arts usually adopt GAN (Generative Adversarial Networks) models.

Computational Efficiency Image Captioning +2

Enhancing Factorization Machines with Generalized Metric Learning

1 code implementation20 Jun 2020 Yangyang Guo, Zhiyong Cheng, Jiazheng Jing, Yanpeng Lin, Liqiang Nie, Meng Wang

Traditional FMs adopt the inner product to model the second-order interactions between different attributes, which are represented via feature vectors.

Attribute Metric Learning +1

Unsupervised Vehicle Re-identification with Progressive Adaptation

no code implementations20 Jun 2020 Jinjia Peng, Yang Wang, Huibing Wang, Zhao Zhang, Xianping Fu, Meng Wang

For PAL, a data adaptation module is employed for source domain, which generates the images with similar data distribution to unlabeled target domain as ``pseudo target samples''.

Unsupervised Vehicle Re-Identification Vehicle Re-Identification

An Edge Information and Mask Shrinking Based Image Inpainting Approach

no code implementations11 Jun 2020 Huali Xu, Xiangdong Su, Meng Wang, Xiang Hao, Guanglai Gao

The mask shrinking strategy is employed in the image completion model to track the areas to be repaired.

Image Inpainting valid

How to Retrain Recommender System? A Sequential Meta-Learning Method

1 code implementation27 May 2020 Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li, Yongdong Zhang

Nevertheless, normal training on new data only may easily cause overfitting and forgetting issues, since the new data is of a smaller scale and contains fewer information on long-term user preference.

Meta-Learning Recommendation Systems

Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation

no code implementations24 May 2020 Le Wu, Yonghui Yang, Lei Chen, Defu Lian, Richang Hong, Meng Wang

The transfer network is designed to approximate the learned item embeddings from graph neural networks by taking each item's visual content as input, in order to tackle the new segment problem in the test phase.

Transfer Learning

Try This Instead: Personalized and Interpretable Substitute Recommendation

no code implementations19 May 2020 Tong Chen, Hongzhi Yin, Guanhua Ye, Zi Huang, Yang Wang, Meng Wang

Then, by treating attributes as the bridge between users and items, we can thoroughly model the user-item preferences (i. e., personalization) and item-item relationships (i. e., substitution) for recommendation.

Attribute Collaborative Filtering +1

SimpleMKKM: Simple Multiple Kernel K-means

1 code implementation11 May 2020 Xinwang Liu, En Zhu, Jiyuan Liu, Timothy Hospedales, Yang Wang, Meng Wang

We propose a simple yet effective multiple kernel clustering algorithm, termed simple multiple kernel k-means (SimpleMKKM).

Clustering

Memory-Augmented Relation Network for Few-Shot Learning

no code implementations9 May 2020 Jun He, Richang Hong, Xueliang Liu, Mingliang Xu, Zheng-Jun Zha, Meng Wang

Metric-based few-shot learning methods concentrate on learning transferable feature embedding that generalizes well from seen categories to unseen categories under the supervision of limited number of labelled instances.

Few-Shot Learning Metric Learning +2

Deep Multimodal Neural Architecture Search

1 code implementation25 Apr 2020 Zhou Yu, Yuhao Cui, Jun Yu, Meng Wang, DaCheng Tao, Qi Tian

Most existing works focus on a single task and design neural architectures manually, which are highly task-specific and hard to generalize to different tasks.

Image-text matching Neural Architecture Search +4

Person Re-Identification via Active Hard Sample Mining

no code implementations10 Apr 2020 Xin Xu, Lei Liu, Weifeng Liu, Meng Wang, Ruimin Hu

To alleviate such a problem, we present an active hard sample mining framework via training an effective re-ID model with the least labeling efforts.

Person Re-Identification

Iterative Context-Aware Graph Inference for Visual Dialog

1 code implementation CVPR 2020 Dan Guo, Hui Wang, Hanwang Zhang, Zheng-Jun Zha, Meng Wang

Visual dialog is a challenging task that requires the comprehension of the semantic dependencies among implicit visual and textual contexts.

Graph Attention Graph Embedding +2

More Grounded Image Captioning by Distilling Image-Text Matching Model

1 code implementation CVPR 2020 Yuanen Zhou, Meng Wang, Daqing Liu, Zhenzhen Hu, Hanwang Zhang

To improve the grounding accuracy while retaining the captioning quality, it is expensive to collect the word-region alignment as strong supervision.

Image Captioning Image-text matching +4

Reinforced Negative Sampling over Knowledge Graph for Recommendation

1 code implementation12 Mar 2020 Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Meng Wang, Tat-Seng Chua

Properly handling missing data is a fundamental challenge in recommendation.

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