Search Results for author: Xiang Li

Found 253 papers, 87 papers with code

Towards Robust Neural Machine Translation with Iterative Scheduled Data-Switch Training

1 code implementation COLING 2022 Zhongjian Miao, Xiang Li, Liyan Kang, Wen Zhang, Chulun Zhou, Yidong Chen, Bin Wang, Min Zhang, Jinsong Su

Most existing methods on robust neural machine translation (NMT) construct adversarial examples by injecting noise into authentic examples and indiscriminately exploit two types of examples.

Machine Translation NMT +1

融合情感分析的隐式反问句识别模型(Implicit Rhetorical Questions Recognition Model Combined with Sentiment Analysis)

no code implementations CCL 2021 Xiang Li, Chengwei Liu, Xiaoxu Zhu

“反问是现代汉语中一种常用的修辞手法, 根据是否含有反问标记可分为显式反问句与隐式反问句。其中隐式反问句表达的情感更为丰富, 表现形式也十分复杂, 对隐式反问句的识别更具挑战性。本文首先扩充了汉语反问句语料库, 语料库规模达到10000余句, 接着针对隐式反问句的特点, 提出了一种融合情感分析的隐式反问句识别模型。模型考虑了句子的语义信息, 上下文信息, 并借助情感分析任务辅助识别隐式反问句。实验结果表明, 本文提出的模型在隐式反问句识别任务上取得了良好的性能。”

Sentiment Analysis

BIT-Xiaomi’s System for AutoSimTrans 2022

no code implementations NAACL (AutoSimTrans) 2022 Mengge Liu, Xiang Li, Bao Chen, Yanzhi Tian, Tianwei Lan, Silin Li, Yuhang Guo, Jian Luan, Bin Wang

This system paper describes the BIT-Xiaomi simultaneous translation system for Autosimtrans 2022 simultaneous translation challenge.

Chunking Data Augmentation +1

Gait Recognition from a Single Image using a Phase-Aware Gait Cycle Reconstruction Network

no code implementations ECCV 2020 Chi Xu, Yasushi Makihara, Xiang Li, Yasushi Yagi, Jianfeng Lu

Specifically, a phase estimation network is introduced for the input single image, and the gait cycle reconstruction network exploits the estimated phase to mitigate the dependence of an encoded feature on the phase of that single image.

Gait Recognition

Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional Network

1 code implementation ACL 2022 Bin Liang, Chenwei Lou, Xiang Li, Min Yang, Lin Gui, Yulan He, Wenjie Pei, Ruifeng Xu

Then, the descriptions of the objects are served as a bridge to determine the importance of the association between the objects of image modality and the contextual words of text modality, so as to build a cross-modal graph for each multi-modal instance.

Association Sarcasm Detection

JointCL: A Joint Contrastive Learning Framework for Zero-Shot Stance Detection

1 code implementation ACL 2022 Bin Liang, Qinglin Zhu, Xiang Li, Min Yang, Lin Gui, Yulan He, Ruifeng Xu

In this paper, we propose a joint contrastive learning (JointCL) framework, which consists of stance contrastive learning and target-aware prototypical graph contrastive learning.

Contrastive Learning Stance Detection

Meta-Learning Siamese Network for Few-Shot Text Classification

no code implementations5 Feb 2023 Chengcheng Han, Yuhe Wang, Yingnan Fu, Xiang Li, Minghui Qiu, Ming Gao, Aoying Zhou

Few-shot learning has been used to tackle the problem of label scarcity in text classification, of which meta-learning based methods have shown to be effective, such as the prototypical networks (PROTO).

Structure Flow-Guided Network for Real Depth Super-Resolution

no code implementations31 Jan 2023 Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li, Jian Yang

Specifically, our framework consists of a cross-modality flow-guided upsampling network (CFUNet) and a flow-enhanced pyramid edge attention network (PEANet).

Depth Estimation Depth Prediction +1

Recurrent Structure Attention Guidance for Depth Super-Resolution

no code implementations31 Jan 2023 Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li, Jian Yang

Second, instead of the coarse concatenation guidance, we propose a recurrent structure attention block, which iteratively utilizes the latest depth estimation and the image features to jointly select clear patterns and boundaries, aiming at providing refined guidance for accurate depth recovery.

Depth Estimation Super-Resolution

SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

no code implementations29 Jan 2023 Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao

In this paper, to comprehensively enhance the performance of generative graph SSL against other GCL models on both unsupervised and supervised learning tasks, we propose the SeeGera model, which is based on the family of self-supervised variational graph auto-encoder (VGAE).

Contrastive Learning Self-Supervised Learning +1

Towards Spatial Equilibrium Object Detection

1 code implementation14 Jan 2023 Zhaohui Zheng, Yuming Chen, Qibin Hou, Xiang Li, Ming-Ming Cheng

In this paper, we study the spatial disequilibrium problem of modern object detectors and propose to quantify this ``spatial bias'' by measuring the detection performance over zones.

object-detection Object Detection

DLGSANet: Lightweight Dynamic Local and Global Self-Attention Networks for Image Super-Resolution

no code implementations5 Jan 2023 Xiang Li, Jinshan Pan, Jinhui Tang, Jiangxin Dong

We develop a hybrid dynamic-Transformer block(HDTB) that integrates the MHDLSA and SparseGSA for both local and global feature exploration.

Image Reconstruction Image Super-Resolution

Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Weighted Negative Samples

1 code implementation28 Dec 2022 Jianxiang Yu, Xiang Li

We take node embeddings in the coarse view as anchors, and construct positive and negative samples from the fine-grained view.

Contrastive Learning Node Clustering

Recovering Surveillance Video Using RF Cues

no code implementations27 Dec 2022 Xiang Li, Rabih Younes

We make use of an auto-encoder-based structure to extract pose features from WiFi frames.

Video Generation

Near-optimal Policy Identification in Active Reinforcement Learning

no code implementations19 Dec 2022 Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic

Many real-world reinforcement learning tasks require control of complex dynamical systems that involve both costly data acquisition processes and large state spaces.

reinforcement-learning reinforcement Learning

One-Stage Cascade Refinement Networks for Infrared Small Target Detection

1 code implementation16 Dec 2022 Yimian Dai, Xiang Li, Fei Zhou, Yulei Qian, Yaohong Chen, Jian Yang

Finally, we present a new research benchmark for infrared small target detection, consisting of the SIRST-V2 dataset of real-world, high-resolution single-frame targets, the normalized contrast evaluation metric, and the DeepInfrared toolkit for detection.

LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving

no code implementations7 Dec 2022 Xiang Li, Junbo Yin, Botian Shi, Yikang Li, Ruigang Yang, Jianbing Shen

In this paper, we present a more artful framework, LiDAR-guided Weakly Supervised Instance Segmentation (LWSIS), which leverages the off-the-shelf 3D data, i. e., Point Cloud, together with the 3D boxes, as natural weak supervisions for training the 2D image instance segmentation models.

Autonomous Driving Instance Segmentation +4

Curriculum Temperature for Knowledge Distillation

1 code implementation29 Nov 2022 Zheng Li, Xiang Li, Lingfeng Yang, Borui Zhao, RenJie Song, Lei Luo, Jun Li, Jian Yang

In this paper, we propose a simple curriculum-based technique, termed Curriculum Temperature for Knowledge Distillation (CTKD), which controls the task difficulty level during the student's learning career through a dynamic and learnable temperature.

Knowledge Distillation

Panoramic Video Salient Object Detection with Ambisonic Audio Guidance

no code implementations26 Nov 2022 Xiang Li, Haoyuan Cao, Shijie Zhao, Junlin Li, Li Zhang, Bhiksha Raj

In this paper, we aim to tackle the video salient object detection problem for panoramic videos, with their corresponding ambisonic audios.

object-detection Salient Object Detection +1

Instance-level Heterogeneous Domain Adaptation for Limited-labeled Sketch-to-Photo Retrieval

1 code implementation IEEE Transactions on Multimedia 2020 Fan Yang, Yang Wu, Zheng Wang, Xiang Li, Sakriani Sakti, Satoshi Nakamura

Therefore, previous works pre-train their models on rich-labeled photo retrieval data (i. e., source domain) and then fine-tune them on the limited-labeled sketch-to-photo retrieval data (i. e., target domain).

Domain Adaptation Image Retrieval +1

Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentors

no code implementations23 Nov 2022 Ryan Burgert, Kanchana Ranasinghe, Xiang Li, Michael S. Ryoo

Recent diffusion-based generative models combined with vision-language models are capable of creating realistic images from natural language prompts.

Unsupervised Semantic Segmentation

DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion

no code implementations20 Nov 2022 Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation.

Depth Completion Depth Estimation +1

Realization of Causal Representation Learning to Adjust Confounding Bias in Latent Space

no code implementations15 Nov 2022 Jia Li, Xiang Li, Xiaowei Jia, Michael Steinbach, Vipin Kumar

Causal graphs are usually considered in a 2D plane, but it has rarely been noticed that within multiple relatively independent timelines, which is comparatively common in causality machine learning, the individual-level differences may lead to Causal Representation Bias (CRB).

Representation Learning

Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

no code implementations7 Nov 2022 Andrey Ignatov, Radu Timofte, Maurizio Denna, Abdel Younes, Ganzorig Gankhuyag, Jingang Huh, Myeong Kyun Kim, Kihwan Yoon, Hyeon-Cheol Moon, Seungho Lee, Yoonsik Choe, Jinwoo Jeong, Sungjei Kim, Maciej Smyl, Tomasz Latkowski, Pawel Kubik, Michal Sokolski, Yujie Ma, Jiahao Chao, Zhou Zhou, Hongfan Gao, Zhengfeng Yang, Zhenbing Zeng, Zhengyang Zhuge, Chenghua Li, Dan Zhu, Mengdi Sun, Ran Duan, Yan Gao, Lingshun Kong, Long Sun, Xiang Li, Xingdong Zhang, Jiawei Zhang, Yaqi Wu, Jinshan Pan, Gaocheng Yu, Jin Zhang, Feng Zhang, Zhe Ma, Hongbin Wang, Hojin Cho, Steve Kim, Huaen Li, Yanbo Ma, Ziwei Luo, Youwei Li, Lei Yu, Zhihong Wen, Qi Wu, Haoqiang Fan, Shuaicheng Liu, Lize Zhang, Zhikai Zong, Jeremy Kwon, Junxi Zhang, Mengyuan Li, Nianxiang Fu, Guanchen Ding, Han Zhu, Zhenzhong Chen, Gen Li, Yuanfan Zhang, Lei Sun, Dafeng Zhang, Neo Yang, Fitz Liu, Jerry Zhao, Mustafa Ayazoglu, Bahri Batuhan Bilecen, Shota Hirose, Kasidis Arunruangsirilert, Luo Ao, Ho Chun Leung, Andrew Wei, Jie Liu, Qiang Liu, Dahai Yu, Ao Li, Lei Luo, Ce Zhu, Seongmin Hong, Dongwon Park, Joonhee Lee, Byeong Hyun Lee, Seunggyu Lee, Se Young Chun, Ruiyuan He, Xuhao Jiang, Haihang Ruan, Xinjian Zhang, Jing Liu, Garas Gendy, Nabil Sabor, Jingchao Hou, Guanghui He

While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints.

Image Super-Resolution

TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization

no code implementations31 Oct 2022 Xiang Li, Junchi Yang, Niao He

Adaptive gradient methods have shown their ability to adjust the stepsizes on the fly in a parameter-agnostic manner, and empirically achieve faster convergence for solving minimization problems.

Disentangled and Robust Representation Learning for Bragging Classification in Social Media

no code implementations27 Oct 2022 Xiang Li, Yucheng Zhou

Researching bragging behavior on social media arouses interest of computational (socio) linguists.

Representation Learning

Pixel-Aligned Non-parametric Hand Mesh Reconstruction

no code implementations17 Oct 2022 Shijian Jiang, Guwen Han, Danhang Tang, Yang Zhou, Xiang Li, Jiming Chen, Qi Ye

The decoder aggregate both local image features in pixels and geometric features in vertices.

Contact2Grasp: 3D Grasp Synthesis via Hand-Object Contact Constraint

no code implementations17 Oct 2022 Haoming Li, Xinzhuo Lin, Yang Zhou, Xiang Li, Yuchi Huo, Jiming Chen, Qi Ye

To tackle the challenge, we introduce an intermediate variable for grasp contact areas to constrain the grasp generation; in other words, we factorize the mapping into two sequential stages by assuming that grasping poses are fully constrained given contact maps: 1) we first learn contact map distributions to generate the potential contact maps for grasps; 2) then learn a mapping from the contact maps to the grasping poses.

Grasp Generation Robotic Grasping

Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding

1 code implementation16 Oct 2022 Jianing Wang, Wenkang Huang, Qiuhui Shi, Hongbin Wang, Minghui Qiu, Xiang Li, Ming Gao

In this paper, to address these problems, we introduce a seminal knowledge prompting paradigm and further propose a knowledge-prompting-based PLM framework KP-PLM.

Language Modelling Natural Language Understanding

Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications

1 code implementation15 Oct 2022 Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael Steinbach, Christopher Duffy, John Nieber, Vipin Kumar

To address this issue, we further propose a new strategy which augments a training segment with an initial value of the target variable from the timestep right before the starting of the training segment.

Probabilistic Inverse Modeling: An Application in Hydrology

no code implementations12 Oct 2022 Somya Sharma, Rahul Ghosh, Arvind Renganathan, Xiang Li, Snigdhansu Chatterjee, John Nieber, Christopher Duffy, Vipin Kumar

We propose uncertainty based learning method that offers 6\% improvement in $R^2$ for streamflow prediction (forward modeling) from inverse model inferred basin characteristic estimates, 17\% reduction in uncertainty (40\% in presence of noise) and 4\% higher coverage rate for basin characteristics.

CofeNet: Context and Former-Label Enhanced Net for Complicated Quotation Extraction

1 code implementation COLING 2022 Yequan Wang, Xiang Li, Aixin Sun, Xuying Meng, Huaming Liao, Jiafeng Guo

CofeNet is able to extract complicated quotations with components of variable lengths and complicated structures.

Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based Decoder

1 code implementation COLING 2022 Fangyu Lei, Shizhu He, Xiang Li, Jun Zhao, Kang Liu

In the real-world question answering scenarios, hybrid form combining both tabular and textual contents has attracted more and more attention, among which numerical reasoning problem is one of the most typical and challenging problems.

Question Answering

Learning a General Clause-to-Clause Relationships for Enhancing Emotion-Cause Pair Extraction

no code implementations29 Aug 2022 Hang Chen, Xinyu Yang, Xiang Li

To learn it applicably, we propose a general clause-level encoding model named EA-GAT comprising E-GAT and Activation Sort.

Emotion-Cause Pair Extraction

Towards Cross-speaker Reading Style Transfer on Audiobook Dataset

no code implementations10 Aug 2022 Xiang Li, Changhe Song, Xianhao Wei, Zhiyong Wu, Jia Jia, Helen Meng

This paper aims to introduce a chunk-wise multi-scale cross-speaker style model to capture both the global genre and the local prosody in audiobook speeches.

Style Transfer

SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization

1 code implementation19 Jul 2022 Ningyi Liao, Dingheng Mo, Siqiang Luo, Xiang Li, Pengcheng Yin

Recent advances in data processing have stimulated the demand for learning graphs of very large scales.

Graph Embedding Graph Learning

Online Video Instance Segmentation via Robust Context Fusion

no code implementations12 Jul 2022 Xiang Li, Jinglu Wang, Xiaohao Xu, Bhiksha Raj, Yan Lu

We propose a robust context fusion network to tackle VIS in an online fashion, which predicts instance segmentation frame-by-frame with a few preceding frames.

Instance Segmentation Semantic Segmentation +1

DTG-SSOD: Dense Teacher Guidance for Semi-Supervised Object Detection

1 code implementation12 Jul 2022 Gang Li, Xiang Li, Yujie Wang, Yichao Wu, Ding Liang, Shanshan Zhang

Specifically, we propose the Inverse NMS Clustering (INC) and Rank Matching (RM) to instantiate the dense supervision, without the widely used, conventional sparse pseudo labels.

object-detection Object Detection +1

RAW-GNN: RAndom Walk Aggregation based Graph Neural Network

no code implementations28 Jun 2022 Di Jin, Rui Wang, Meng Ge, Dongxiao He, Xiang Li, Wei Lin, Weixiong Zhang

Due to the homophily assumption of Graph Convolutional Networks (GCNs) that these methods use, they are not suitable for heterophily graphs where nodes with different labels or dissimilar attributes tend to be adjacent.

Representation Learning

Neural Neural Textures Make Sim2Real Consistent

no code implementations27 Jun 2022 Ryan Burgert, Jinghuan Shang, Xiang Li, Michael Ryoo

Unpaired image translation algorithms can be used for sim2real tasks, but many fail to generate temporally consistent results.

Translation

Dual Power Spectrum Manifold and Toeplitz HPD Manifold: Enhancement and Analysis for Matrix CFAR Detection

no code implementations24 Jun 2022 Hao Wu, Yongqiang Cheng, Xixi Chen, Zheng Yang, Xiang Li, Hongqiang Wang

These advantages benefit from the geometry of the Toeplitz Hermitian positive definite (HPD) manifold $\mathcal{M}_{\mathcal{T}H_{++}}$, but the sophisticated geometry also results in some challenges for geometric detectors, such as the implementation of the enhanced detector to improve the SCR (signal-to-clutter ratio) and the analysis of the detection performance.

Bear the Query in Mind: Visual Grounding with Query-conditioned Convolution

no code implementations18 Jun 2022 Chonghan Chen, Qi Jiang, Chih-Hao Wang, Noel Chen, Haohan Wang, Xiang Li, Bhiksha Raj

With our proposed QCM, the downstream fusion module receives visual features that are more discriminative and focused on the desired object described in the expression, leading to more accurate predictions.

Visual Grounding

Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization

no code implementations1 Jun 2022 Junchi Yang, Xiang Li, Niao He

Adaptive algorithms like AdaGrad and AMSGrad are successful in nonconvex optimization owing to their parameter-agnostic ability -- requiring no a priori knowledge about problem-specific parameters nor tuning of learning rates.

CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning

no code implementations30 May 2022 Di Jin, Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan

As most of the existing graph neural networks yield effective graph representations of a single graph, little effort has been made for jointly learning two graph representations and calculating their similarity score.

Collaborative Filtering Graph Classification +4

Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality

1 code implementation20 May 2022 Xiang Li, Wenhai Wang, Lingfeng Yang, Jian Yang

Masked AutoEncoder (MAE) has recently led the trends of visual self-supervision area by an elegant asymmetric encoder-decoder design, which significantly optimizes both the pre-training efficiency and fine-tuning accuracy.

Object Detection

AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System

no code implementations19 May 2022 Xiang Li, Xiaojiang Zhou, Yao Xiao, Peihao Huang, Dayao Chen, Sheng Chen, Yunsen Xian

Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages.

Information Retrieval Neural Architecture Search +3

Lexical Knowledge Internalization for Neural Dialog Generation

1 code implementation ACL 2022 Zhiyong Wu, Wei Bi, Xiang Li, Lingpeng Kong, Ben Kao

We propose knowledge internalization (KI), which aims to complement the lexical knowledge into neural dialog models.

Contrastive Learning

Speech Emotion Recognition with Global-Aware Fusion on Multi-scale Feature Representation

1 code implementation12 Apr 2022 Wenjing Zhu, Xiang Li

Speech Emotion Recognition (SER) is a fundamental task to predict the emotion label from speech data.

Speech Emotion Recognition

An End-to-end Chinese Text Normalization Model based on Rule-guided Flat-Lattice Transformer

1 code implementation31 Mar 2022 Wenlin Dai, Changhe Song, Xiang Li, Zhiyong Wu, Huashan Pan, Xiulin Li, Helen Meng

Inspired by Flat-LAttice Transformer (FLAT), we propose an end-to-end Chinese text normalization model, which accepts Chinese characters as direct input and integrates expert knowledge contained in rules into the neural network, both contribute to the superior performance of proposed model for the text normalization task.

PseCo: Pseudo Labeling and Consistency Training for Semi-Supervised Object Detection

1 code implementation30 Mar 2022 Gang Li, Xiang Li, Yujie Wang, Yichao Wu, Ding Liang, Shanshan Zhang

Specifically, for pseudo labeling, existing works only focus on the classification score yet fail to guarantee the localization precision of pseudo boxes; For consistency training, the widely adopted random-resize training only considers the label-level consistency but misses the feature-level one, which also plays an important role in ensuring the scale invariance.

object-detection Object Detection +1

Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search

1 code implementation29 Mar 2022 Zhifang Fan, Dan Ou, Yulong Gu, Bairan Fu, Xiang Li, Wentian Bao, Xin-yu Dai, Xiaoyi Zeng, Tao Zhuang, Qingwen Liu

In this paper, we propose a new perspective for context-aware users' behavior modeling by including the whole page-wisely exposed products and the corresponding feedback as contextualized page-wise feedback sequence.

Click-Through Rate Prediction Denoising

A Learning Convolutional Neural Network Approach for Network Robustness Prediction

no code implementations20 Mar 2022 Yang Lou, Ruizi Wu, Junli Li, Lin Wang, Xiang Li, Guanrong Chen

Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors; 2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability; 3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations; 4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures.

Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion

no code implementations18 Mar 2022 Zhiqiang Yan, Xiang Li, Kun Wang, Zhenyu Zhang, Jun Li, Jian Yang

To deal with the PDC task, we train a deep network that takes both depth and image as inputs for the dense panoramic depth recovery.

Depth Completion Transfer Learning

EEG based Emotion Recognition: A Tutorial and Review

no code implementations16 Mar 2022 Xiang Li, Yazhou Zhang, Prayag Tiwari, Dawei Song, Bin Hu, Meihong Yang, Zhigang Zhao, Neeraj Kumar, Pekka Marttinen

Hence, in this paper, we review from the perspective of researchers who try to take the first step on this topic.

EEG Emotion Recognition

RecursiveMix: Mixed Learning with History

1 code implementation14 Mar 2022 Lingfeng Yang, Xiang Li, Borui Zhao, RenJie Song, Jian Yang

In semantic segmentation, RM also surpasses the baseline and CutMix by 1. 9 and 1. 1 mIoU points under UperNet on ADE20K, respectively.

object-detection Object Detection +1

Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information

1 code implementation CVPR 2022 Lingfeng Yang, Xiang Li, RenJie Song, Borui Zhao, Juntian Tao, Shihao Zhou, Jiajun Liang, Jian Yang

Therefore, it is helpful to leverage additional information, e. g., the locations and dates for data shooting, which can be easily accessible but rarely exploited.

Fine-Grained Image Classification

A density peaks clustering algorithm with sparse search and K-d tree

no code implementations2 Mar 2022 Yunxiao Shan, Shu Li, Fuxiang Li, Yuxin Cui, Shuai Li, Ming Zhou, Xiang Li

It is proved that the algorithm can effectively reduce the computational complexity of the original DPC from $O(n^2K)$ to $O(n(n^{1-1/K}+k))$.

WSLRec: Weakly Supervised Learning for Neural Sequential Recommendation Models

no code implementations28 Feb 2022 Jingwei Zhuo, Bin Liu, Xiang Li, Han Zhu, Xiaoqiang Zhu

Motivated by the observation that model-free methods like behavioral retargeting (BR) and item-based collaborative filtering (ItemCF) hit different parts of the user-item relevance compared to neural sequential recommendation models, we propose a novel model-agnostic training approach called WSLRec, which adopts a three-stage framework: pre-training, top-$k$ mining, and fine-tuning.

Collaborative Filtering Sequential Recommendation

Multi-modal Sensor Fusion for Auto Driving Perception: A Survey

no code implementations6 Feb 2022 Keli Huang, Botian Shi, Xiang Li, Xin Li, Siyuan Huang, Yikang Li

Multi-modal fusion is a fundamental task for the perception of an autonomous driving system, which has recently intrigued many researchers.

Autonomous Driving object-detection +2

Forgery Attack Detection in Surveillance Video Streams Using Wi-Fi Channel State Information

no code implementations24 Jan 2022 Yong Huang, Xiang Li, Wei Wang, Tao Jiang, Qian Zhang

The cybersecurity breaches expose surveillance video streams to forgery attacks, under which authentic streams are falsified to hide unauthorized activities.

Time Series Video Forensics

Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems

1 code implementation10 Jan 2022 Lianghao Xia, Chao Huang, Yong Xu, Huance Xu, Xiang Li, WeiGuo Zhang

As the deep learning techniques have expanded to real-world recommendation tasks, many deep neural network based Collaborative Filtering (CF) models have been developed to project user-item interactions into latent feature space, based on various neural architectures, such as multi-layer perceptron, auto-encoder and graph neural networks.

Collaborative Filtering Recommendation Systems

Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning

no code implementations31 Dec 2021 Xiang Li, Dong Li, Ruoming Jin, Gagan Agrawal, Rajiv Ramnath

Though other methods (particularly those based on Laplacian Smoothing) have reported better accuracy, a fundamental limitation of all the work is a lack of scalability.

Deep Clustering Graph Clustering +2

Polyak-Ruppert-Averaged Q-Learning is Statistically Efficient

no code implementations29 Dec 2021 Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan

We study synchronous Q-learning with Polyak-Ruppert averaging (a. k. a., averaged Q-learning) in a $\gamma$-discounted MDP.

Q-Learning

Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation

no code implementations9 Dec 2021 Gang Li, Xiang Li, Yujie Wang, Shanshan Zhang, Yichao Wu, Ding Liang

Based on the two observations, we propose Rank Mimicking (RM) and Prediction-guided Feature Imitation (PFI) for distilling one-stage detectors, respectively.

Knowledge Distillation Model Compression +2

Hybrid Instance-aware Temporal Fusion for Online Video Instance Segmentation

no code implementations3 Dec 2021 Xiang Li, Jinglu Wang, Xiao Li, Yan Lu

Based on this representation, we introduce a cropping-free temporal fusion approach to model the temporal consistency between video frames.

Image Segmentation Instance Segmentation +2

Reinforcement Learning Enhanced Explainer for Graph Neural Networks

no code implementations NeurIPS 2021 Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li

To address these issues, we propose a RL-enhanced GNN explainer, RG-Explainer, which consists of three main components: starting point selection, iterative graph generation and stopping criteria learning.

Combinatorial Optimization Graph Generation +2

Automated Pulmonary Embolism Detection from CTPA Images Using an End-to-End Convolutional Neural Network

no code implementations10 Nov 2021 Yi Lin, Jianchao Su, Xiang Wang, Xiang Li, Jingen Liu, Kwang-Ting Cheng, Xin Yang

We have evaluated our approach using the 20 CTPA test dataset from the PE challenge, achieving a sensitivity of 78. 9%, 80. 7% and 80. 7% at 2 false positives per volume at 0mm, 2mm and 5mm localization error, which is superior to the state-of-the-art methods.

Pulmonary Embolism Detection

Generative Dynamic Patch Attack

1 code implementation8 Nov 2021 Xiang Li, Shihao Ji

Extensive experiments on VGGFace, Traffic Sign and ImageNet show that GDPA achieves higher attack success rates than state-of-the-art patch attacks, while adversarially trained model with GDPA demonstrates superior robustness to adversarial patch attacks than competing methods.

Improved Loss Function-Based Prediction Method of Extreme Temperatures in Greenhouses

no code implementations2 Nov 2021 Liao Qu, Shuaiqi Huang, Yunsong Jia, Xiang Li

By increasing the weight of extreme temperature samples and reducing the possibility of misjudging extreme temperature as normal, the proposed loss function can enhance the prediction results in extreme situations.

Unified Style Transfer

1 code implementation20 Oct 2021 Guanjie Huang, Hongjian He, Xiang Li, Xingchen Li, Ziang Liu

Currently, it is hard to compare and evaluate different style transfer algorithms due to chaotic definitions of style and the absence of agreed objective validation methods in the study of style transfer.

Philosophy Style Transfer +1

Video Instance Segmentation by Instance Flow Assembly

no code implementations20 Oct 2021 Xiang Li, Jinglu Wang, Xiao Li, Yan Lu

Instance segmentation is a challenging task aiming at classifying and segmenting all object instances of specific classes.

Instance Segmentation Object Localization +2

StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning

1 code implementation12 Oct 2021 Jinghuan Shang, Kumara Kahatapitiya, Xiang Li, Michael S. Ryoo

Reinforcement Learning (RL) can be considered as a sequence modeling task: given a sequence of past state-action-reward experiences, an agent predicts a sequence of next actions.

Imitation Learning Inductive Bias +3

Feasible Architecture for Quantum Fully Convolutional Networks

no code implementations5 Oct 2021 Yusui Chen, Wenhao Hu, Xiang Li

Fully convolutional networks are robust in performing semantic segmentation, with many applications from signal processing to computer vision.

Semantic Segmentation

Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation

no code implementations1 Oct 2021 Zheng Li, Xiang Li, Lingfeng Yang, Jian Yang, Zhigeng Pan

Knowledge distillation usually transfers the knowledge from a pre-trained cumbersome teacher network to a compact student network, which follows the classical teacher-teaching-student paradigm.

Self-Knowledge Distillation

Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology

no code implementations14 Sep 2021 Rahul Ghosh, Arvind Renganathan, Kshitij Tayal, Xiang Li, Ankush Khandelwal, Xiaowei Jia, Chris Duffy, John Neiber, Vipin Kumar

Furthermore, we show that KGSSL is relatively more robust to distortion than baseline methods, and outperforms the baseline model by 35\% when plugging in KGSSL inferred characteristics.

Self-Supervised Learning

Fine-Grained Few Shot Learning with Foreground Object Transformation

no code implementations13 Sep 2021 Chaofei Wang, Shiji Song, Qisen Yang, Xiang Li, Gao Huang

As a data augmentation method, FOT can be conveniently applied to any existing few shot learning algorithm and greatly improve its performance on FG-FSL tasks.

Data Augmentation Few-Shot Learning +1

Cost-Effective Federated Learning in Mobile Edge Networks

no code implementations12 Sep 2021 Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas

Federated learning (FL) is a distributed learning paradigm that enables a large number of mobile devices to collaboratively learn a model under the coordination of a central server without sharing their raw data.

Federated Learning

RigNet: Repetitive Image Guided Network for Depth Completion

no code implementations29 Jul 2021 Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

However, blurry guidance in the image and unclear structure in the depth still impede the performance of the image guided frameworks.

Depth Completion Depth Estimation +1

Learn to Learn Metric Space for Few-Shot Segmentation of 3D Shapes

no code implementations7 Jul 2021 Xiang Li, Lingjing Wang, Yi Fang

To achieve this, we treat the shape segmentation as a point labeling problem in the metric space.

Meta-Learning

A More Compact Object Detector Head Network with Feature Enhancement and Relational Reasoning

no code implementations28 Jun 2021 Wenchao Zhang, Chong Fu, Xiangshi Chang, Tengfei Zhao, Xiang Li, Chiu-Wing Sham

Without losing generality, we can also build a more lighter head network for other multi-stage detectors by assembling our method.

object-detection Object Detection +1

Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding

no code implementations20 Jun 2021 Chaolei Tan, Zihang Lin, Jian-Fang Hu, Xiang Li, Wei-Shi Zheng

We propose an effective two-stage approach to tackle the problem of language-based Human-centric Spatio-Temporal Video Grounding (HC-STVG) task.

Spatio-Temporal Video Grounding Video Grounding

The Image Local Autoregressive Transformer

1 code implementation NeurIPS 2021 Chenjie Cao, Yuxin Hong, Xiang Li, Chengrong Wang, Chengming Xu, xiangyang xue, Yanwei Fu

To address these limitations, we propose a novel model -- image Local Autoregressive Transformer (iLAT), to better facilitate the locally guided image synthesis.

Image Generation

Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning

no code implementations31 May 2021 Binbin Xie, Jinsong Su, Yubin Ge, Xiang Li, Jianwei Cui, Junfeng Yao, Bin Wang

However, such a decoder only exploits the preorder traversal based preceding actions, which are insufficient to ensure correct action predictions.

Code Generation

Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation

no code implementations ACL 2021 Zhiyong Wu, Lingpeng Kong, Wei Bi, Xiang Li, Ben Kao

A neural multimodal machine translation (MMT) system is one that aims to perform better translation by extending conventional text-only translation models with multimodal information.

Multimodal Machine Translation Translation

PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text

1 code implementation2 May 2021 Wenhai Wang, Enze Xie, Xiang Li, Xuebo Liu, Ding Liang, Zhibo Yang, Tong Lu, Chunhua Shen

By systematically comparing with existing scene text representations, we show that our kernel representation can not only describe arbitrarily-shaped text but also well distinguish adjacent text.

Scene Text Detection Text Spotting

Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood

no code implementations12 Apr 2021 Cong Li, Min Shi, Bo Qu, Xiang Li

In this paper, we propose a deep attributed network representation learning via attribute enhanced neighborhood (DANRL-ANE) model to improve the robustness and effectiveness of node representations.

Link Prediction Node Classification +1

Towards Multi-Scale Style Control for Expressive Speech Synthesis

no code implementations8 Apr 2021 Xiang Li, Changhe Song, Jingbei Li, Zhiyong Wu, Jia Jia, Helen Meng

This paper introduces a multi-scale speech style modeling method for end-to-end expressive speech synthesis.

Expressive Speech Synthesis Style Transfer

Development and Validation of a Deep Learning Model for Prediction of Severe Outcomes in Suspected COVID-19 Infection

no code implementations21 Mar 2021 Varun Buch, Aoxiao Zhong, Xiang Li, Marcio Aloisio Bezerra Cavalcanti Rockenbach, Dufan Wu, Hui Ren, Jiahui Guan, Andrew Liteplo, Sayon Dutta, Ittai Dayan, Quanzheng Li

Predictive risk scores for COVID-19 severe outcomes ("CO-RISK" score) were derived from model output and evaluated on the testing dataset, as well as compared to human performance.

Management

Structure-Enhanced Meta-Learning For Few-Shot Graph Classification

1 code implementation5 Mar 2021 Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li, Xiangnan He

Graph classification is a highly impactful task that plays a crucial role in a myriad of real-world applications such as molecular property prediction and protein function prediction. Aiming to handle the new classes with limited labeled graphs, few-shot graph classification has become a bridge of existing graph classification solutions and practical usage. This work explores the potential of metric-based meta-learning for solving few-shot graph classification. We highlight the importance of considering structural characteristics in the solution and propose a novel framework which explicitly considers global structure and local structure of the input graph.

Classification General Classification +4

Privacy-Preserving Distributed SVD via Federated Power

no code implementations1 Mar 2021 Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang

The low communication and computation power of such devices, and the possible privacy breaches of users' sensitive data make the computation of SVD challenging.

BIG-bench Machine Learning Federated Learning +1

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

9 code implementations ICCV 2021 Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao

Unlike the recently-proposed Transformer model (e. g., ViT) that is specially designed for image classification, we propose Pyramid Vision Transformer~(PVT), which overcomes the difficulties of porting Transformer to various dense prediction tasks.

Image Classification Instance Segmentation +3

vrCAPTCHA: Exploring CAPTCHA Designs in Virtual Reality

no code implementations24 Feb 2021 Xiang Li, Yuzheng Chen, Rakesh Patibanda, Florian 'Floyd' Mueller

With the popularity of online access in virtual reality (VR) devices, it will become important to investigate exclusive and interactive CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) designs for VR devices.

Human-Computer Interaction

SceneRec: Scene-Based Graph Neural Networks for Recommender Systems

no code implementations12 Feb 2021 Gang Wang, Ziyi Guo, Xiang Li, Dawei Yin, Shuai Ma

Collaborative filtering has been largely used to advance modern recommender systems to predict user preference.

Collaborative Filtering Recommendation Systems +1

Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications

no code implementations5 Jan 2021 Xiang Li, Zhihua Zhang

In this work, we study a novel class of projection-based algorithms for linearly constrained problems (LCPs) which have a lot of applications in statistics, optimization, and machine learning.

Distributed Optimization Privacy Preserving

Towards Cross-Modal Forgery Detection and Localization on Live Surveillance Videos

no code implementations4 Jan 2021 Yong Huang, Xiang Li, Wei Wang, Tao Jiang, Qian Zhang

Traditional video forensics approaches can detect and localize forgery traces in each video frame using computationally-expensive spatial-temporal analysis, while falling short in real-time verification of live video feeds.

Time Series Video Forensics Cryptography and Security

Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More

1 code implementation1 Jan 2021 Xiulong Yang, Hui Ye, Yang Ye, Xiang Li, Shihao Ji

We show that our Generative MMC (GMMC) can be trained discriminatively, generatively, or jointly for image classification and generation.

Adversarial Robustness Classification +4

Box-To-Box Transformation for Modeling Joint Hierarchies

no code implementations1 Jan 2021 Shib Sankar Dasgupta, Xiang Li, Michael Boratko, Dongxu Zhang, Andrew McCallum

In Patel et al. (2020), the authors demonstrate that only the transitive reduction is required, and further extend box embeddings to capture joint hierarchies by augmenting the graph with new nodes.

Knowledge Graphs

Leveraging Meta-path Contexts for Classification in Heterogeneous Information Networks

no code implementations18 Dec 2020 Xiang Li, Danhao Ding, Ben Kao, Yizhou Sun, Nikos Mamoulis

A heterogeneous information network (HIN) has as vertices objects of different types and as edges the relations between objects, which are also of various types.

Classification General Classification +2

Cost-Effective Federated Learning Design

no code implementations15 Dec 2020 Bing Luo, Xiang Li, Shiqiang Wang, Jianwei Huang, Leandros Tassiulas

In this paper, we analyze how to design adaptive FL that optimally chooses these essential control variables to minimize the total cost while ensuring convergence.

Federated Learning

Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling

1 code implementation6 Dec 2020 Jia-Qi Yang, Xiang Li, Shuguang Han, Tao Zhuang, De-Chuan Zhan, Xiaoyi Zeng, Bin Tong

To strike a balance in this trade-off, we propose Elapsed-Time Sampling Delayed Feedback Model (ES-DFM), which models the relationship between the observed conversion distribution and the true conversion distribution.

Physics Guided Machine Learning Methods for Hydrology

no code implementations2 Dec 2020 Ankush Khandelwal, Shaoming Xu, Xiang Li, Xiaowei Jia, Michael Stienbach, Christopher Duffy, John Nieber, Vipin Kumar

The goal of this work is to incorporate our understanding of physical processes and constraints in hydrology into machine learning algorithms, and thus bridge the performance gap while reducing the need for large amounts of data compared to traditional data-driven approaches.

BIG-bench Machine Learning

Neuron-level Structured Pruning using Polarization Regularizer

1 code implementation NeurIPS 2020 Tao Zhuang, Zhixuan Zhang, Yuheng Huang, Xiaoyi Zeng, Kai Shuang, Xiang Li

Experimentally, we show that structured pruning using polarization regularizer achieves much better results than using L1 regularizer.

Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19

no code implementations26 Nov 2020 Aoxiao Zhong, Xiang Li, Dufan Wu, Hui Ren, Kyungsang Kim, YoungGon Kim, Varun Buch, Nir Neumark, Bernardo Bizzo, Won Young Tak, Soo Young Park, Yu Rim Lee, Min Kyu Kang, Jung Gil Park, Byung Seok Kim, Woo Jin Chung, Ning Guo, Ittai Dayan, Mannudeep K. Kalra, Quanzheng Li

These results demonstrate our deep metric learning based image retrieval model is highly efficient in the CXR retrieval, diagnosis and prognosis, and thus has great clinical value for the treatment and management of COVID-19 patients.

Image Retrieval Management +2

PC-GAIN: Pseudo-label Conditional Generative Adversarial Imputation Networks for Incomplete Data

1 code implementation16 Nov 2020 Yufeng Wang, Dan Li, Xiang Li, Min Yang

Further, this classifier is incorporated into the generative adversarial framework to help the generator to yield higher quality imputation results.

Imputation Pseudo Label

Retrieving and ranking short medical questions with two stages neural matching model

no code implementations16 Nov 2020 Xiang Li, Xinyu Fu, Zheng Lu, Ruibin Bai, Uwe Aickelin, Peiming Ge, Gong Liu

Internet hospital is a rising business thanks to recent advances in mobile web technology and high demand of health care services.

Information Retrieval Retrieval

3D Meta-Registration: Learning to Learn Registration of 3D Point Clouds

no code implementations22 Oct 2020 Lingjing Wang, Yu Hao, Xiang Li, Yi Fang

In this paper, we propose a meta-learning based 3D registration model, named 3D Meta-Registration, that is capable of rapidly adapting and well generalizing to new 3D registration tasks for unseen 3D point clouds.

Meta-Learning Point Cloud Registration

3D Meta Point Signature: Learning to Learn 3D Point Signature for 3D Dense Shape Correspondence

no code implementations21 Oct 2020 Hao Huang, Lingjing Wang, Xiang Li, Yi Fang

In this paper, we propose a novel meta-learning based 3D point signature model, named 3Dmetapointsignature (MEPS) network, that is capable of learning robust point signatures in 3D shapes.

3D Dense Shape Correspondence Meta-Learning

Reading Comprehension as Natural Language Inference: A Semantic Analysis

no code implementations4 Oct 2020 Anshuman Mishra, Dhruvesh Patel, Aparna Vijayakumar, Xiang Li, Pavan Kapanipathi, Kartik Talamadupula

We transform the one of the largest available MRC dataset (RACE) to an NLI form, and compare the performances of a state-of-the-art model (RoBERTa) on both these forms.

Natural Language Inference Question Answering +1

Deep-3DAligner: Unsupervised 3D Point Set Registration Network With Optimizable Latent Vector

no code implementations29 Sep 2020 Lingjing Wang, Xiang Li, Yi Fang

Point cloud registration is the process of aligning a pair of point sets via searching for a geometric transformation.

Point Cloud Registration

Looking Beyond Sentence-Level Natural Language Inference for Downstream Tasks

no code implementations18 Sep 2020 Anshuman Mishra, Dhruvesh Patel, Aparna Vijayakumar, Xiang Li, Pavan Kapanipathi, Kartik Talamadupula

In recent years, the Natural Language Inference (NLI) task has garnered significant attention, with new datasets and models achieving near human-level performance on it.

Natural Language Inference Question Answering +1

Unsupervised Partial Point Set Registration via Joint Shape Completion and Registration

no code implementations11 Sep 2020 Xiang Li, Lingjing Wang, Yi Fang

To bridge the performance gaps between partial point set registration with full point set registration, we proposed to incorporate a shape completion network to benefit the registration process.

Object Detection in the Context of Mobile Augmented Reality

no code implementations15 Aug 2020 Xiang Li, Yuan Tian, Fuyao Zhang, Shuxue Quan, Yi Xu

Ordinary object detection approaches process information from the images only, and they are oblivious to the camera pose with regard to the environment and the scale of the environment.

object-detection Real-Time Object Detection

Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data

no code implementations14 Aug 2020 Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang

In this paper, we focus on nonlinear learning with kernels, and propose a federated doubly stochastic kernel learning (FDSKL) algorithm for vertically partitioned data.

BIG-bench Machine Learning Federated Learning

Robust Image Matching By Dynamic Feature Selection

no code implementations13 Aug 2020 Hao Huang, Jianchun Chen, Xiang Li, Lingjing Wang, Yi Fang

Recent works introduce convolutional neural networks (CNNs) to extract high-level feature maps and find correspondences through feature matching.

Decision Making

GP-Aligner: Unsupervised Non-rigid Groupwise Point Set Registration Based On Optimized Group Latent Descriptor

no code implementations25 Jul 2020 Lingjing Wang, Xiang Li, Yi Fang

More specifically, for a given group we first define an optimizable Group Latent Descriptor (GLD) to characterize the gruopwise relationship among a group of point sets.

Simulating multi-exit evacuation using deep reinforcement learning

no code implementations11 Jul 2020 Dong Xu, Xiao Huang, Joseph Mango, Xiang Li, Zhenlong Li

We propose a multi-exit evacuation simulation based on Deep Reinforcement Learning (DRL), referred to as the MultiExit-DRL, which involves in a Deep Neural Network (DNN) framework to facilitate state-to-action mapping.

reinforcement-learning reinforcement Learning

Xiaomi's Submissions for IWSLT 2020 Open Domain Translation Task

no code implementations WS 2020 Yuhui Sun, Mengxue Guo, Xiang Li, Jianwei Cui, Bin Wang

This paper describes the Xiaomi{'}s submissions to the IWSLT20 shared open domain translation task for Chinese{\textless}-{\textgreater}Japanese language pair.

Domain Adaptation Knowledge Distillation +2

DeepTracking-Net: 3D Tracking with Unsupervised Learning of Continuous Flow

no code implementations24 Jun 2020 Shuaihang Yuan, Xiang Li, Yi Fang

In this paper, we aim at handling the problem of 3D tracking, which provides the tracking of the consecutive frames of 3D shapes.

3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction

no code implementations24 Jun 2020 Shuaihang Yuan, Xiang Li, Anthony Tzes, Yi Fang

To approach this problem, we propose a self-supervised approach that leverages the power of the deep neural network to learn a continuous flow function of 3D point clouds that can predict temporally consistent future motions and naturally bring out the correspondences among consecutive point clouds at the same time.

motion prediction

Disentangling User Interest and Conformity for Recommendation with Causal Embedding

3 code implementations19 Jun 2020 Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Depeng Jin, Yong Li

We further demonstrate that the learned embeddings successfully capture the desired causes, and show that DICE guarantees the robustness and interpretability of recommendation.

Causal Inference

Unsupervised Learning of Global Registration of Temporal Sequence of Point Clouds

no code implementations17 Jun 2020 Lingjing Wang, Yi Shi, Xiang Li, Yi Fang

Global registration of point clouds aims to find an optimal alignment of a sequence of 2D or 3D point sets.

Few-shot Object Detection on Remote Sensing Images

no code implementations14 Jun 2020 Jingyu Deng, Xiang Li, Yi Fang

In this paper, we introduce a few-shot learning-based method for object detection on remote sensing images where only a few annotated samples are provided for the unseen object categories.

Few-Shot Learning Few-Shot Object Detection +1

Unsupervised Learning of 3D Point Set Registration

no code implementations11 Jun 2020 Lingjing Wang, Xiang Li, Yi Fang

Moreover, for a pair of source and target point sets, existing deep learning mechanisms require explicitly designed encoders to extract both deep spatial features from unstructured point clouds and their spatial correlation representation, which is further fed to a decoder to regress the desired geometric transformation for point set alignment.

Point Cloud Registration

Geometry-Aware Segmentation of Remote Sensing Images via Implicit Height Estimation

no code implementations10 Jun 2020 Xiang Li, Lingjing Wang, Yi Fang

Recent studies have shown the benefits of using additional elevation data (e. g., DSM) for enhancing the performance of the semantic segmentation of aerial images.

Semantic Segmentation

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

7 code implementations NeurIPS 2020 Xiang Li, Wenhai Wang, Lijun Wu, Shuo Chen, Xiaolin Hu, Jun Li, Jinhui Tang, Jian Yang

Specifically, we merge the quality estimation into the class prediction vector to form a joint representation of localization quality and classification, and use a vector to represent arbitrary distribution of box locations.

Dense Object Detection General Classification

CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data

1 code implementation8 Jun 2020 Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester

We study the problem of applying spectral clustering to cluster multi-scale data, which is data whose clusters are of various sizes and densities.

FGCRec: Fine-Grained Geographical Characteristics Modeling for Point-of-Interest Recommendation

1 code implementation IEEE International Conference on Communications 2020 Yijun Su, Xiang Li, Baoping Liu, Daren Zha, Ji Xiang, Wei Tang and Neng Gao.

With the popularity of location-based social networks (LBSNs), Point-of-Interest (POI) recommendation has become an essential location-based service to help people explore novel locations.

Recommendation Systems

Height estimation from single aerial images using a deep ordinal regression network

no code implementations4 Jun 2020 Xiang Li, Mingyang Wang, Yi Fang

Previous researches have extensively studied the problem of height estimation from aerial images based on stereo or multi-view image matching.

Change Detection Management +1

Gait Recognition via Semi-supervised Disentangled Representation Learning to Identity and Covariate Features

no code implementations CVPR 2020 Xiang Li, Yasushi Makihara, Chi Xu, Yasushi Yagi, Mingwu Ren

Existing gait recognition approaches typically focus on learning identity features that are invariant to covariates (e. g., the carrying status, clothing, walking speed, and viewing angle) and seldom involve learning features from the covariate aspect, which may lead to failure modes when variations due to the covariate overwhelm those due to the identity.

Disentanglement Gait Recognition

Convolutional Neural Network for Behavioral Modeling and Predistortion of Wideband Power Amplifiers

no code implementations20 May 2020 Xin Hu, Zhijun Liu, Xiaofei Yu, Yulong Zhao, WenHua Chen, Biao Hu, Xuekun Du, Xiang Li, Mohamed Helaoui, Weidong Wang, Fadhel M. Ghannouchi

We design a pre-designed filter using the convolutional layer to extract the basis functions required for the PA forward or reverse modeling.

One-Shot Object Detection without Fine-Tuning

1 code implementation8 May 2020 Xiang Li, Lin Zhang, Yau Pun Chen, Yu-Wing Tai, Chi-Keung Tang

Deep learning has revolutionized object detection thanks to large-scale datasets, but their object categories are still arguably very limited.

Metric Learning object-detection +1

A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label Learning

1 code implementation3 May 2020 Xiang Li, Songcan Chen

In aligning, we characterize the global and local structures of multiple labels to be high-rank and low-rank, respectively.

Model Selection Multi-Label Learning

Airborne LiDAR Point Cloud Classification with Graph Attention Convolution Neural Network

no code implementations20 Apr 2020 Congcong Wen, Xiang Li, Xiaojing Yao, Ling Peng, Tianhe Chi

To achieve point cloud classification, previous studies proposed point cloud deep learning models that can directly process raw point clouds based on PointNet-like architectures.

General Classification Graph Attention +2

TEDL: A Text Encryption Method Based on Deep Learning

1 code implementation9 Mar 2020 Xiang Li, Peng Wang

Firstly, both communication parties establish a word vector table by training a deep learning model according to specified hyperparameters.

Adversarial Multimodal Representation Learning for Click-Through Rate Prediction

no code implementations7 Mar 2020 Xiang Li, Chao Wang, Jiwei Tan, Xiaoyi Zeng, Dan Ou, Bo Zheng

Finally, we achieve the multimodal item representations by combining both modality-specific and modality-invariant representations.

Click-Through Rate Prediction Representation Learning

Communication-Efficient Distributed SVD via Local Power Iterations

no code implementations19 Feb 2020 Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang

As a practical surrogate of OPT, sign-fixing, which uses a diagonal matrix with $\pm 1$ entries as weights, has better computation complexity and stability in experiments.

Distributed Computing

Representing Joint Hierarchies with Box Embeddings

1 code implementation AKBC 2020 Dhruvesh Patel, Shib Sankar Dasgupta, Michael Boratko, Xiang Li, Luke Vilnis, Andrew McCallum

Box Embeddings [Vilnis et al., 2018, Li et al., 2019] represent concepts with hyperrectangles in $n$-dimensional space and are shown to be capable of modeling tree-like structures efficiently by training on a large subset of the transitive closure of the WordNet hypernym graph.

ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems

1 code implementation ACL 2020 Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang

We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems.

Task-Oriented Dialogue Systems