Search Results for author: Bing Li

Found 113 papers, 44 papers with code

When does Further Pre-training MLM Help? An Empirical Study on Task-Oriented Dialog Pre-training

1 code implementation EMNLP (insights) 2021 Qi Zhu, Yuxian Gu, Lingxiao Luo, Bing Li, Cheng Li, Wei Peng, Minlie Huang, Xiaoyan Zhu

Further pre-training language models on in-domain data (domain-adaptive pre-training, DAPT) or task-relevant data (task-adaptive pre-training, TAPT) before fine-tuning has been shown to improve downstream tasks’ performances.

CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators

no code implementations23 Jan 2024 Songyun Qu, Shixin Zhao, Bing Li, Yintao He, Xuyi Cai, Lei Zhang, Ying Wang

Based on the proposed abstraction, CIM-MLC can compile tasks onto a wide range of CIM accelerators having different devices, architectures, and programming interfaces.

Scheduling

GMC-IQA: Exploiting Global-correlation and Mean-opinion Consistency for No-reference Image Quality Assessment

no code implementations19 Jan 2024 Zewen Chen, Juan Wang, Bing Li, Chunfeng Yuan, Weiming Hu, Junxian Liu, Peng Li, Yan Wang, Youqun Zhang, Congxuan Zhang

Due to the subjective nature of image quality assessment (IQA), assessing which image has better quality among a sequence of images is more reliable than assigning an absolute mean opinion score for an image.

No-Reference Image Quality Assessment

Set Prediction Guided by Semantic Concepts for Diverse Video Captioning

no code implementations25 Dec 2023 Yifan Lu, Ziqi Zhang, Chunfeng Yuan, Peng Li, Yan Wang, Bing Li, Weiming Hu

Each caption in the set is attached to a concept combination indicating the primary semantic content of the caption and facilitating element alignment in set prediction.

Video Captioning

Dataset Distillation via Adversarial Prediction Matching

1 code implementation14 Dec 2023 Mingyang Chen, Bo Huang, Junda Lu, Bing Li, Yi Wang, Minhao Cheng, Wei Wang

This ensures the memory efficiency of our method and provides a flexible tradeoff between time and memory budgets, allowing us to distil ImageNet-1K using a minimum of only 6. 5GB of GPU memory.

Point Cloud Self-supervised Learning via 3D to Multi-view Masked Autoencoder

1 code implementation17 Nov 2023 Zhimin Chen, Yingwei Li, Longlong Jing, Liang Yang, Bing Li

However, a notable limitation of these approaches is that they do not fully utilize the multi-view attributes inherent in 3D point clouds, which is crucial for a deeper understanding of 3D structures.

3D Object Classification 3D Object Detection +3

Knowledge Graph Construction in Power Distribution Networks

no code implementations15 Nov 2023 Xiang Li, Che Wang, Bing Li, Hao Chen, Sizhe Li

In this paper, we propose a method for knowledge graph construction in power distribution networks.

Entity Linking graph construction +1

ZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking

1 code implementation NeurIPS 2023 Yutong Kou, Jin Gao, Bing Li, Gang Wang, Weiming Hu, Yizheng Wang, Liang Li

To this end, we non-uniformly resize the cropped image to have a smaller input size while the resolution of the area where the target is more likely to appear is higher and vice versa.

Visual Tracking

Automatic Animation of Hair Blowing in Still Portrait Photos

no code implementations ICCV 2023 Wenpeng Xiao, Wentao Liu, Yitong Wang, Bernard Ghanem, Bing Li

Considering the complexity of hair structure, we innovatively treat hair wisp extraction as an instance segmentation problem, where a hair wisp is referred to as an instance.

Image Animation Instance Segmentation +2

Logic Design of Neural Networks for High-Throughput and Low-Power Applications

no code implementations19 Sep 2023 Kangwei Xu, Grace Li Zhang, Ulf Schlichtmann, Bing Li

However, under a given area constraint, the number of MAC units in such platforms is limited, so MAC units have to be reused to perform MAC operations in a neural network.

On Exact Bayesian Credible Sets for Classification and Pattern Recognition

no code implementations21 Aug 2023 Chaegeun Song, Bing Li

As a result, there is as of today no general way to construct an exact credible set for classification.

Bayesian Inference Classification +1

Learning to Identify Critical States for Reinforcement Learning from Videos

1 code implementation ICCV 2023 Haozhe Liu, Mingchen Zhuge, Bing Li, Yuhui Wang, Francesco Faccio, Bernard Ghanem, Jürgen Schmidhuber

Recent work on deep reinforcement learning (DRL) has pointed out that algorithmic information about good policies can be extracted from offline data which lack explicit information about executed actions.

reinforcement-learning

Spectral Regularized Kernel Goodness-of-Fit Tests

no code implementations8 Aug 2023 Omar Hagrass, Bharath K. Sriperumbudur, Bing Li

Maximum mean discrepancy (MMD) has enjoyed a lot of success in many machine learning and statistical applications, including non-parametric hypothesis testing, because of its ability to handle non-Euclidean data.

Test

On Sufficient Graphical Models

no code implementations10 Jul 2023 Bing Li, Kyongwon Kim

We introduce a sufficient graphical model by applying the recently developed nonlinear sufficient dimension reduction techniques to the evaluation of conditional independence.

Dimensionality Reduction Variable Selection

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

1 code implementation30 Jun 2023 Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, Bernard Ghanem

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors.

Image to 3D

CATS: A Pragmatic Chinese Answer-to-Sequence Dataset with Large Scale and High Quality

no code implementations20 Jun 2023 Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Rongyu Cao, Binhua Li, Fei Huang, Yongbin Li

To alleviate these limitations, in this paper, we present CATS, a pragmatic Chinese answer-to-sequence dataset with large scale and high quality.

Dynamically Masked Discriminator for Generative Adversarial Networks

1 code implementation13 Jun 2023 Wentian Zhang, Haozhe Liu, Bing Li, Jinheng Xie, Yawen Huang, Yuexiang Li, Yefeng Zheng, Bernard Ghanem

By treating the generated data in training as a stream, we propose to detect whether the discriminator slows down the learning of new knowledge in generated data.

Continual Learning

Computational and Storage Efficient Quadratic Neurons for Deep Neural Networks

no code implementations10 Jun 2023 Chuangtao Chen, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li

Deep neural networks (DNNs) have been widely deployed across diverse domains such as computer vision and natural language processing.

Image Classification Semantic Segmentation

Exploiting Correlations Between Contexts and Definitions with Multiple Definition Modeling

no code implementations24 May 2023 Linhan Zhang, Qian Chen, Wen Wang, Yuxin Jiang, Bing Li, Wei Wang, Xin Cao

In this paper, we carefully design a new task called Multiple Definition Modeling (MDM) that pool together all contexts and definition of target words.

Component-aware anomaly detection framework for adjustable and logical industrial visual inspection

1 code implementation15 May 2023 Tongkun Liu, Bing Li, Xiao Du, Bingke Jiang, Xiao Jin, Liuyi Jin, Zhuo Zhao

Meanwhile, segmenting a product image into multiple components provides a novel perspective for industrial visual inspection, demonstrating great potential in model customization, noise resistance, and anomaly classification.

Anomaly Classification Anomaly Detection +1

Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models

1 code implementation NeurIPS 2023 Zhimin Chen, Longlong Jing, Yingwei Li, Bing Li

Foundation models have achieved remarkable results in 2D and language tasks like image segmentation, object detection, and visual-language understanding.

3D Object Detection Image Captioning +7

CVRecon: Rethinking 3D Geometric Feature Learning For Neural Reconstruction

no code implementations ICCV 2023 Ziyue Feng, Liang Yang, Pengsheng Guo, Bing Li

Recent advances in neural reconstruction using posed image sequences have made remarkable progress.

LLM as A Robotic Brain: Unifying Egocentric Memory and Control

no code implementations19 Apr 2023 Jinjie Mai, Jun Chen, Bing Li, Guocheng Qian, Mohamed Elhoseiny, Bernard Ghanem

In this paper, we propose a novel and generalizable framework called LLM-Brain: using Large-scale Language Model as a robotic brain to unify egocentric memory and control.

Embodied Question Answering Language Modelling +2

PowerPruning: Selecting Weights and Activations for Power-Efficient Neural Network Acceleration

no code implementations24 Mar 2023 Richard Petri, Grace Li Zhang, Yiran Chen, Ulf Schlichtmann, Bing Li

To address this challenge, we propose PowerPruning, a novel method to reduce power consumption in digital neural network accelerators by selecting weights that lead to less power consumption in MAC operations.

Efficient Neural Network

Understanding Bugs in Multi-Language Deep Learning Frameworks

no code implementations5 Mar 2023 Zengyang Li, Sicheng Wang, Wenshuo Wang, Peng Liang, Ran Mo, Bing Li

Third, we found that 28. 6%, 31. 4%, and 16. 0% of bugs in MXNet, PyTorch, and TensorFlow are MPL bugs, respectively; the PL combination of Python and C/C++ is most used in fixing more than 92% MPL bugs in all DLFs.

Improving GAN Training via Feature Space Shrinkage

1 code implementation2 Mar 2023 Haozhe Liu, Wentian Zhang, Bing Li, Haoqian Wu, Nanjun He, Yawen Huang, Yuexiang Li, Bernard Ghanem, Yefeng Zheng

The evaluation results demonstrate that our AdaptiveMix can facilitate the training of GANs and effectively improve the image quality of generated samples.

Out of Distribution (OOD) Detection

Mean Parity Fair Regression in RKHS

1 code implementation21 Feb 2023 Shaokui Wei, Jiayin Liu, Bing Li, Hongyuan Zha

We study the fair regression problem under the notion of Mean Parity (MP) fairness, which requires the conditional mean of the learned function output to be constant with respect to the sensitive attributes.

Fairness regression

Variation Enhanced Attacks Against RRAM-based Neuromorphic Computing System

no code implementations20 Feb 2023 Hao Lv, Bing Li, Lei Zhang, Cheng Liu, Ying Wang

The RRAM-based neuromorphic computing system has amassed explosive interests for its superior data processing capability and energy efficiency than traditional architectures, and thus being widely used in many data-centric applications.

Adversarial Attack

Plan-then-Seam: Towards Efficient Table-to-Text Generation

1 code implementation10 Feb 2023 Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Binhua Li, Yongbin Li

Table-to-text generation aims at automatically generating text to help people conveniently obtain salient information in tables.

Table-to-Text Generation

AdaptiveMix: Improving GAN Training via Feature Space Shrinkage

1 code implementation CVPR 2023 Haozhe Liu, Wentian Zhang, Bing Li, Haoqian Wu, Nanjun He, Yawen Huang, Yuexiang Li, Bernard Ghanem, Yefeng Zheng

The evaluation results demonstrate that our AdaptiveMix can facilitate the training of GANs and effectively improve the image quality of generated samples.

Out of Distribution (OOD) Detection

AUNet: Learning Relations Between Action Units for Face Forgery Detection

no code implementations CVPR 2023 Weiming Bai, Yufan Liu, Zhipeng Zhang, Bing Li, Weiming Hu

Observing that face manipulation may alter the relation between different facial action units (AU), we propose the Action Units Relation Learning framework to improve the generality of forgery detection.

DeepFake Detection Face Swapping +1

ViLEM: Visual-Language Error Modeling for Image-Text Retrieval

no code implementations CVPR 2023 Yuxin Chen, Zongyang Ma, Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Weiming Hu, XiaoHu Qie, Jianping Wu

ViLEM then enforces the model to discriminate the correctness of each word in the plausible negative texts and further correct the wrong words via resorting to image information.

Contrastive Learning Retrieval +3

Spectral Regularized Kernel Two-Sample Tests

no code implementations19 Dec 2022 Omar Hagrass, Bharath K. Sriperumbudur, Bing Li

First, we show that the popular MMD (maximum mean discrepancy) two-sample test is not optimal in terms of the separation boundary measured in Hellinger distance.

Test Vocal Bursts Valence Prediction

Hierarchical Terrain Attention and Multi-Scale Rainfall Guidance For Flood Image Prediction

no code implementations4 Dec 2022 Feifei Wang, Yong Wang, Bing Li, Qidong Huang, Shaoqing Chen

With the deterioration of climate, the phenomenon of rain-induced flooding has become frequent.

Be Careful with Rotation: A Uniform Backdoor Pattern for 3D Shape

no code implementations28 Nov 2022 Linkun Fan, Fazhi He, Qing Guo, Wei Tang, Xiaolin Hong, Bing Li

As a result, backdoor pattern designed for one certain 3D data structure will be disable for other data structures of the same 3D scene.

Backdoor Attack

Class-based Quantization for Neural Networks

no code implementations27 Nov 2022 Wenhao Sun, Grace Li Zhang, Huaxi Gu, Bing Li, Ulf Schlichtmann

In the proposed method, the importance score of each filter or neuron with respect to the number of classes in the dataset is first evaluated.

Quantization

CorrectNet: Robustness Enhancement of Analog In-Memory Computing for Neural Networks by Error Suppression and Compensation

no code implementations27 Nov 2022 Amro Eldebiky, Grace Li Zhang, Georg Boecherer, Bing Li, Ulf Schlichtmann

These acceleration platforms rely on analog properties of the devices and thus suffer from process variations and noise.

SteppingNet: A Stepping Neural Network with Incremental Accuracy Enhancement

no code implementations27 Nov 2022 Wenhao Sun, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Huaxi Gu, Bing Li, Ulf Schlichtmann

In such platforms, neural networks need to provide acceptable results quickly and the accuracy of the results should be able to be enhanced dynamically according to the computational resources available in the computing system.

Autonomous Vehicles

Decoupled Mixup for Generalized Visual Recognition

1 code implementation26 Oct 2022 Haozhe Liu, Wentian Zhang, Jinheng Xie, Haoqian Wu, Bing Li, Ziqi Zhang, Yuexiang Li, Yawen Huang, Bernard Ghanem, Yefeng Zheng

Since the observation is that noise-prone regions such as textural and clutter backgrounds are adverse to the generalization ability of CNN models during training, we enhance features from discriminative regions and suppress noise-prone ones when combining an image pair.

Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detection

1 code implementation26 Oct 2022 Tongkun Liu, Bing Li, Zhuo Zhao, Xiao Du, Bingke Jiang, Leqi Geng

The model with an overly strong generalization capability can even well reconstruct the abnormal regions, making them less distinguishable, while the model with a poor generalization capability can not reconstruct those changeable high-frequency components in the normal regions, which ultimately leads to false positives.

Anomaly Detection Denoising

Class-Level Confidence Based 3D Semi-Supervised Learning

1 code implementation18 Oct 2022 Zhimin Chen, Longlong Jing, Liang Yang, Yingwei Li, Bing Li

Firstly, a dynamic thresholding strategy is proposed to utilize more unlabeled data, especially for low learning status classes.

Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion

1 code implementation COLING 2022 Chen Chen, YuFei Wang, Bing Li, Kwok-Yan Lam

To remedy the KG structure information loss from the "flat" text, we further improve the input representations of entities and relations, and the inference algorithm in KG-S2S.

Knowledge Graph Completion

Combating Mode Collapse in GANs via Manifold Entropy Estimation

1 code implementation25 Aug 2022 Haozhe Liu, Bing Li, Haoqian Wu, Hanbang Liang, Yawen Huang, Yuexiang Li, Bernard Ghanem, Yefeng Zheng

In this paper, we propose a novel training pipeline to address the mode collapse issue of GANs.

Cross-Architecture Knowledge Distillation

no code implementations12 Jul 2022 Yufan Liu, Jiajiong Cao, Bing Li, Weiming Hu, Jingting Ding, Liang Li

However, most existing knowledge distillation methods only consider homologous-architecture distillation, such as distilling knowledge from CNN to CNN.

Knowledge Distillation

Nonlinear Sufficient Dimension Reduction for Distribution-on-Distribution Regression

1 code implementation11 Jul 2022 Qi Zhang, Bing Li, Lingzhou Xue

We introduce a new approach to nonlinear sufficient dimension reduction in cases where both the predictor and the response are distributional data, modeled as members of a metric space.

Dimensionality Reduction regression

Narrowing the Gap: Improved Detector Training with Noisy Location Annotations

1 code implementation12 Jun 2022 Shaoru Wang, Jin Gao, Bing Li, Weiming Hu

Experiments for both synthesized and real-world scenarios consistently demonstrate the effectiveness of our approach, e. g., our method increases the degraded performance of the FCOS detector from 33. 6% AP to 35. 6% AP on COCO.

object-detection Object Detection

Representation Learning for Compressed Video Action Recognition via Attentive Cross-modal Interaction with Motion Enhancement

no code implementations7 May 2022 Bing Li, Jiaxin Chen, Dongming Zhang, Xiuguo Bao, Di Huang

To address the two issues above, this paper proposes a novel framework, namely Attentive Cross-modal Interaction Network with Motion Enhancement (MEACI-Net).

Action Recognition Denoising +2

SubGraph Networks based Entity Alignment for Cross-lingual Knowledge Graph

no code implementations7 May 2022 Shanqing Yu, Shihan Zhang, Jianlin Zhang, Jiajun Zhou, Qi Xuan, Bing Li, Xiaojuan Hu

Cross-lingual knowledge graph entity alignment aims to discover the cross-lingual links in the multi-language KGs, which is of great significance to the NLP applications and multi-language KGs fusion.

Entity Alignment Knowledge Graphs

Improving Visual Grounding with Visual-Linguistic Verification and Iterative Reasoning

1 code implementation CVPR 2022 Li Yang, Yan Xu, Chunfeng Yuan, Wei Liu, Bing Li, Weiming Hu

They base the visual grounding on the features from pre-generated proposals or anchors, and fuse these features with the text embeddings to locate the target mentioned by the text.

Attribute object-detection +2

CREATE: A Benchmark for Chinese Short Video Retrieval and Title Generation

no code implementations31 Mar 2022 Ziqi Zhang, Yuxin Chen, Zongyang Ma, Zhongang Qi, Chunfeng Yuan, Bing Li, Ying Shan, Weiming Hu

In this paper, we propose to CREATE, the first large-scale Chinese shoRt vidEo retrievAl and Title gEneration benchmark, to facilitate research and application in video titling and video retrieval in Chinese.

Retrieval Video Captioning +1

Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depth

1 code implementation29 Mar 2022 Ziyue Feng, Liang Yang, Longlong Jing, HaiYan Wang, YingLi Tian, Bing Li

Conventional self-supervised monocular depth prediction methods are based on a static environment assumption, which leads to accuracy degradation in dynamic scenes due to the mismatch and occlusion problems introduced by object motions.

Depth Prediction Disentanglement +4

Learning Scene Flow in 3D Point Clouds with Noisy Pseudo Labels

no code implementations23 Mar 2022 Bing Li, Cheng Zheng, Guohao Li, Bernard Ghanem

To provide an alternative, we propose a novel approach that utilizes monocular RGB images and point clouds to generate pseudo scene flow labels for training scene flow networks.

Pseudo Label Self-Supervised Learning

Continual Prompt Tuning for Dialog State Tracking

1 code implementation ACL 2022 Qi Zhu, Bing Li, Fei Mi, Xiaoyan Zhu, Minlie Huang

A desirable dialog system should be able to continually learn new skills without forgetting old ones, and thereby adapt to new domains or tasks in its life cycle.

Continual Learning dialog state tracking +1

Learning Target-aware Representation for Visual Tracking via Informative Interactions

no code implementations7 Jan 2022 Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing, Yilin Lyu, Bing Li, Weiming Hu

The proposed GIM module and InBN mechanism are general and applicable to different backbone types including CNN and Transformer for improvements, as evidenced by our extensive experiments on multiple benchmarks.

Representation Learning Visual Tracking

An additive graphical model for discrete data

no code implementations29 Dec 2021 Jun Tao, Bing Li, Lingzhou Xue

We introduce a nonparametric graphical model for discrete node variables based on additive conditional independence.

Relation

Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking

2 code implementations CVPR 2020 Jin Gao, Yan Lu, Xiaojuan Qi, Yutong Kou, Bing Li, Liang Li, Shan Yu, Weiming Hu

In this paper, we propose a simple yet effective recursive least-squares estimator-aided online learning approach for few-shot online adaptation without requiring offline training.

Continual Learning One-Shot Learning +1

Joint Learning of Visual-Audio Saliency Prediction and Sound Source Localization on Multi-face Videos

1 code implementation5 Nov 2021 Minglang Qiao, Yufan Liu, Mai Xu, Xin Deng, Bing Li, Weiming Hu, Ali Borji

In this paper, we propose a multitask learning method for visual-audio saliency prediction and sound source localization on multi-face video by leveraging visual, audio and face information.

Saliency Prediction

Multimodal Semi-Supervised Learning for 3D Objects

1 code implementation22 Oct 2021 Zhimin Chen, Longlong Jing, Yang Liang, YingLi Tian, Bing Li

This paper explores how the coherence of different modelities of 3D data (e. g. point cloud, image, and mesh) can be used to improve data efficiency for both 3D classification and retrieval tasks.

3D Classification Retrieval

MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction

1 code implementation Findings (ACL) 2022 Linhan Zhang, Qian Chen, Wen Wang, Chong Deng, Shiliang Zhang, Bing Li, Wei Wang, Xin Cao

In this work, we propose a novel unsupervised embedding-based KPE approach, Masked Document Embedding Rank (MDERank), to address this problem by leveraging a mask strategy and ranking candidates by the similarity between embeddings of the source document and the masked document.

Contrastive Learning Document Embedding +4

Dimension Reduction for Fréchet Regression

no code implementations1 Oct 2021 Qi Zhang, Lingzhou Xue, Bing Li

In this paper, we introduce a flexible sufficient dimension reduction (SDR) method for Fr\'echet regression to achieve two purposes: to mitigate the curse of dimensionality caused by high-dimensional predictors and to provide a visual inspection tool for Fr\'echet regression.

Data Visualization Dimensionality Reduction +1

Self-Supervised Modality-Invariant and Modality-Specific Feature Learning for 3D Objects

no code implementations29 Sep 2021 Longlong Jing, Zhimin Chen, Bing Li, YingLi Tian

Our proposed novel self-supervised model learns two types of distinct features: modality-invariant features and modality-specific features.

3D Object Recognition Cross-Modal Retrieval +1

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

2 code implementations20 Sep 2021 Ziyue Feng, Longlong Jing, Peng Yin, YingLi Tian, Bing Li

Unlike the existing methods that use sparse LiDAR mainly in a manner of time-consuming iterative post-processing, our model fuses monocular image features and sparse LiDAR features to predict initial depth maps.

Depth Completion Depth Prediction +3

SDTP: Semantic-aware Decoupled Transformer Pyramid for Dense Image Prediction

no code implementations18 Sep 2021 Zekun Li, Yufan Liu, Bing Li, Weiming Hu, Kebin Wu, Pei Wang

CDI builds the global attention and interaction among different levels in decoupled space which also solves the problem of heavy computation.

Sent2Span: Span Detection for PICO Extraction in the Biomedical Text without Span Annotations

1 code implementation Findings (EMNLP) 2021 Shifeng Liu, Yifang Sun, Bing Li, Wei Wang, Florence T. Bourgeois, Adam G. Dunn

The rapid growth in published clinical trials makes it difficult to maintain up-to-date systematic reviews, which requires finding all relevant trials.

PICO Sentence

Learn to Match: Automatic Matching Network Design for Visual Tracking

1 code implementation ICCV 2021 Zhipeng Zhang, Yihao Liu, Xiao Wang, Bing Li, Weiming Hu

Siamese tracking has achieved groundbreaking performance in recent years, where the essence is the efficient matching operator cross-correlation and its variants.

Visual Tracking

PSE-Match: A Viewpoint-free Place Recognition Method with Parallel Semantic Embedding

no code implementations1 Aug 2021 Peng Yin, Lingyun Xu, Ziyue Feng, Anton Egorov, Bing Li

Accurate localization on autonomous driving cars is essential for autonomy and driving safety, especially for complex urban streets and search-and-rescue subterranean environments where high-accurate GPS is not available.

Autonomous Driving Retrieval

Automatic Construction of Enterprise Knowledge Base

no code implementations EMNLP (ACL) 2021 Junyi Chai, Yujie He, Homa Hashemi, Bing Li, Daraksha Parveen, Ranganath Kondapally, Wenjin Xu

In this paper, we present an automatic knowledge base construction system from large scale enterprise documents with minimal efforts of human intervention.

SCTN: Sparse Convolution-Transformer Network for Scene Flow Estimation

1 code implementation10 May 2021 Bing Li, Cheng Zheng, Silvio Giancola, Bernard Ghanem

We propose a novel scene flow estimation approach to capture and infer 3D motions from point clouds.

Scene Flow Estimation

A Simple and Strong Baseline for Universal Targeted Attacks on Siamese Visual Tracking

no code implementations6 May 2021 Zhenbang Li, Yaya Shi, Jin Gao, Shaoru Wang, Bing Li, Pengpeng Liang, Weiming Hu

In this paper, we show the existence of universal perturbations that can enable the targeted attack, e. g., forcing a tracker to follow the ground-truth trajectory with specified offsets, to be video-agnostic and free from inference in a network.

Visual Tracking

PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling

1 code implementation28 Apr 2021 Li Yang, Yan Xu, Shaoru Wang, Chunfeng Yuan, Ziqi Zhang, Bing Li, Weiming Hu

However, the most suitable positions for inferring different targets, i. e., the object category and boundaries, are generally different.

Object object-detection +1

Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model

1 code implementation ECCV 2020 Yufan Liu, Minglang Qiao, Mai Xu, Bing Li, Weiming Hu, Ali Borji

Inspired by the findings of our investigation, we propose a novel multi-modal video saliency model consisting of three branches: visual, audio and face.

Saliency Prediction

Open-book Video Captioning with Retrieve-Copy-Generate Network

no code implementations CVPR 2021 Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Ying Deng, Weiming Hu

Due to the rapid emergence of short videos and the requirement for content understanding and creation, the video captioning task has received increasing attention in recent years.

Retrieval Video Captioning

AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation

3 code implementations24 Feb 2021 Bing Li, Yuanlue Zhu, Yitong Wang, Chia-Wen Lin, Bernard Ghanem, Linlin Shen

Specifically, a new generator architecture is proposed to simultaneously transfer color/texture styles and transform local facial shapes into anime-like counterparts based on the style of a reference anime-face, while preserving the global structure of the source photo-face.

Face Generation Translation

On Forward Sufficient Dimension Reduction for Categorical and Ordinal Responses

no code implementations11 Feb 2021 Harris Quach, Bing Li

Like other forward regression-based sufficient dimension reduction methods, our approach avoids the relatively stringent distributional requirements necessary for inverse regression alternatives.

Dimensionality Reduction Methodology

FGNET-RH: Fine-Grained Named Entity Typing via Refinement in Hyperbolic Space

no code implementations27 Jan 2021 Muhammad Asif Ali, Yifang Sun, Bing Li, Wei Wang

Fine-Grained Named Entity Typing (FG-NET) aims at classifying the entity mentions into a wide range of entity types (usually hundreds) depending upon the context.

Entity Typing

Cross-Lingual Named Entity Recognition Using Parallel Corpus: A New Approach Using XLM-RoBERTa Alignment

no code implementations26 Jan 2021 Bing Li, Yujie He, Wenjin Xu

We built an entity alignment model on top of XLM-RoBERTa to project the entities detected on the English part of the parallel data to the target language sentences, whose accuracy surpasses all previous unsupervised models.

Cross-Lingual NER Entity Alignment +4

Named Entity Recognition in the Style of Object Detection

no code implementations26 Jan 2021 Bing Li

In this work, we propose a two-stage method for named entity recognition (NER), especially for nested NER.

named-entity-recognition Named Entity Recognition +6

High Quality Disparity Remapping With Two-Stage Warping

no code implementations ICCV 2021 Bing Li, Chia-Wen Lin, Cheng Zheng, Shan Liu, Junsong Yuan, Bernard Ghanem, C.-C. Jay Kuo

In the second stage, we derive another warping model to refine warping results in less important regions by eliminating serious distortions in shape, disparity and 3D structure.

Vocal Bursts Intensity Prediction Vocal Bursts Valence Prediction

Rethinking the competition between detection and ReID in Multi-Object Tracking

4 code implementations23 Oct 2020 Chao Liang, Zhipeng Zhang, Xue Zhou, Bing Li, Shuyuan Zhu, Weiming Hu

However, the inherent differences and relations between detection and re-identification (ReID) are unconsciously overlooked because of treating them as two isolated tasks in the one-shot tracking paradigm.

 Ranked #1 on Multi-Object Tracking on HiEve (using extra training data)

Multi-Object Tracking

Towards Accurate Pixel-wise Object Tracking by Attention Retrieval

1 code implementation6 Aug 2020 Zhipeng Zhang, Bing Li, Weiming Hu, Houwen Peng

We first build a look-up-table (LUT) with the ground-truth mask in the starting frame, and then retrieves the LUT to obtain an attention map for spatial constraints.

Object Object Tracking +2

Object Relational Graph with Teacher-Recommended Learning for Video Captioning

no code implementations CVPR 2020 Ziqi Zhang, Yaya Shi, Chunfeng Yuan, Bing Li, Peijin Wang, Weiming Hu, Zheng-Jun Zha

In this paper, we propose a complete video captioning system including both a novel model and an effective training strategy.

Ranked #8 on Video Captioning on VATEX (using extra training data)

Language Modelling Video Captioning

HAMNER: Headword Amplified Multi-span Distantly Supervised Method for Domain Specific Named Entity Recognition

no code implementations3 Dec 2019 Shifeng Liu, Yifang Sun, Bing Li, Wei Wang, Xiang Zhao

To tackle Named Entity Recognition (NER) tasks, supervised methods need to obtain sufficient cleanly annotated data, which is labor and time consuming.

Boundary Detection named-entity-recognition +2

An Overview of In-memory Processing with Emerging Non-volatile Memory for Data-intensive Applications

no code implementations15 Jun 2019 Bing Li, Bonan Yan, Hai, Li

The conventional von Neumann architecture has been revealed as a major performance and energy bottleneck for rising data-intensive applications.

Multimodal Semantic Attention Network for Video Captioning

no code implementations8 May 2019 Liang Sun, Bing Li, Chunfeng Yuan, Zheng-Jun Zha, Weiming Hu

Inspired by the fact that different modalities in videos carry complementary information, we propose a Multimodal Semantic Attention Network(MSAN), which is a new encoder-decoder framework incorporating multimodal semantic attributes for video captioning.

Attribute General Classification +2

Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

no code implementations ECCV 2018 Yang Du, Chunfeng Yuan, Bing Li, Lili Zhao, Yangxi Li, Weiming Hu

Furthermore, since different layers in a deep network capture feature maps of different scales, we use these feature maps to construct a spatial pyramid and then utilize multi-scale information to obtain more accurate attention scores, which are used to weight the local features in all spatial positions of feature maps to calculate attention maps.

Action Classification Classification +1

Depth-Aware Stereo Video Retargeting

no code implementations CVPR 2018 Bing Li, Chia-Wen Lin, Boxin Shi, Tiejun Huang, Wen Gao, C. -C. Jay Kuo

As compared with traditional video retargeting, stereo video retargeting poses new challenges because stereo video contains the depth information of salient objects and its time dynamics.

Spatio-Temporal Self-Organizing Map Deep Network for Dynamic Object Detection From Videos

no code implementations CVPR 2017 Yang Du, Chunfeng Yuan, Bing Li, Weiming Hu, Stephen Maybank

In dynamic object detection, it is challenging to construct an effective model to sufficiently characterize the spatial-temporal properties of the background.

object-detection Object Detection

Linear Contour Learning: A Method for Supervised Dimension Reduction

no code implementations13 Aug 2014 Bing Li, Hongyuan Zha, Francesca Chiaromonte

We propose a novel approach to sufficient dimension reduction in regression, based on estimating contour directions of negligible variation for the response surface.

Dimensionality Reduction regression

Removing Mixture of Gaussian and Impulse Noise by Patch-Based Weighted Means

no code implementations11 Mar 2014 Haijuan Hu, Bing Li, Quansheng Liu

We first establish a law of large numbers and a convergence theorem in distribution to show the rate of convergence of the non-local means filter for removing Gaussian noise.

Illumination Estimation Based on Bilayer Sparse Coding

no code implementations CVPR 2013 Bing Li, Weihua Xiong, Weiming Hu, Houwen Peng

In this paper, we propose a novel bilayer sparse coding model for illumination estimation that considers image similarity in terms of both low level color distribution and high level image scene content simultaneously.

Color Constancy

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