Search Results for author: Yang Wu

Found 39 papers, 12 papers with code

Mitigating the Inconsistency Between Word Saliency and Model Confidence with Pathological Contrastive Training

no code implementations Findings (ACL) 2022 Pengwei Zhan, Yang Wu, Shaolei Zhou, Yunjian Zhang, Liming Wang

We show that the pathological inconsistency is caused by the representation collapse issue, which means that the representation of the sentences with tokens in different saliency reduced is somehow collapsed, and thus the important words cannot be distinguished from unimportant words in terms of model confidence changing.

Contrastive Learning

ForkGAN: Seeing into the Rainy Night

no code implementations ECCV 2020 Ziqiang Zheng, Yang Wu, Xinran Han, Jianbo Shi

We present a ForkGAN for task-agnostic image translation that can boost multiple vision tasks in adverse weather conditions.

Image Generation object-detection +3

UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection

1 code implementation CVPR 2022 Ye Liu, Siyuan Li, Yang Wu, Chang Wen Chen, Ying Shan, XiaoHu Qie

Finding relevant moments and highlights in videos according to natural language queries is a natural and highly valuable common need in the current video content explosion era.

Highlight Detection Moment Retrieval

Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors

1 code implementation Findings (ACL) 2022 Yang Wu, Yanyan Zhao, Hao Yang, Song Chen, Bing Qin, Xiaohuan Cao, Wenting Zhao

Through further analysis of the ASR outputs, we find that in some cases the sentiment words, the key sentiment elements in the textual modality, are recognized as other words, which makes the sentiment of the text change and hurts the performance of multimodal sentiment models directly.

Automatic Speech Recognition Multimodal Sentiment Analysis +1

a novel attention-based network for fast salient object detection

no code implementations20 Dec 2021 Bin Zhang, Yang Wu, Xiaojing Zhang, Ming Ma

In the current salient object detection network, the most popular method is using U-shape structure.

object-detection Object Detection +1

ACNet: Approaching-and-Centralizing Network for Zero-Shot Sketch-Based Image Retrieval

no code implementations24 Nov 2021 Hao Ren, Ziqiang Zheng, Yang Wu, Hong Lu, Yang Yang, Sai-Kit Yeung

The huge domain gap between sketches and photos and the highly abstract sketch representations pose challenges for sketch-based image retrieval (\underline{SBIR}).

Sketch-Based Image Retrieval

Explore before Moving: A Feasible Path Estimation and Memory Recalling Framework for Embodied Navigation

no code implementations16 Oct 2021 Yang Wu, Shirui Feng, Guanbin Li, Liang Lin

PEMR includes a "looking ahead" process, \textit{i. e.} a visual feature extractor module that estimates feasible paths for gathering 3D navigational information, which is mimicking the human sense of direction.

Common Sense Reasoning Embodied Question Answering +1

Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions

no code implementations30 Aug 2021 Yang Wu, Dingheng Wang, Xiaotong Lu, Fan Yang, Guoqi Li, Weisheng Dong, Jianbo Shi

Visual recognition is currently one of the most important and active research areas in computer vision, pattern recognition, and even the general field of artificial intelligence.

Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting

3 code implementations27 Jul 2021 Changan Wang, Qingyu Song, Boshen Zhang, Yabiao Wang, Ying Tai, Xuyi Hu, Chengjie Wang, Jilin Li, Jiayi Ma, Yang Wu

Therefore, we propose a novel count interval partition criterion called Uniform Error Partition (UEP), which always keeps the expected counting error contributions equal for all intervals to minimize the prediction risk.

Crowd Counting Quantization

SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking

no code implementations24 May 2021 Jinlong Peng, Zhengkai Jiang, Yueyang Gu, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Weiyao Lin

In addition, we add a localization branch to predict the localization accuracy, so that it can work as the replacement of the regression assistance link during inference.

Classification Visual Object Tracking

Uniformity in Heterogeneity: Diving Deep Into Count Interval Partition for Crowd Counting

1 code implementation ICCV 2021 Changan Wang, Qingyu Song, Boshen Zhang, Yabiao Wang, Ying Tai, Xuyi Hu, Chengjie Wang, Jilin Li, Jiayi Ma, Yang Wu

Therefore, we propose a novel count interval partition criterion called Uniform Error Partition (UEP), which always keeps the expected counting error contributions equal for all intervals to minimize the prediction risk.

Crowd Counting Quantization

Detection of magnetic gap in the topological surface states of MnBi2Te4

no code implementations31 Dec 2020 Haoran Ji, Yanzhao Liu, He Wang, Jiawei Luo, Jiaheng Li, Hao Li, Yang Wu, Yong Xu, Jian Wang

An essential ingredient to realize these quantum states is the magnetic gap in the topological surface states induced by the out-of-plane ferromagnetism on the surface of MnBi2Te4.

Materials Science

An Iterative Emotion Interaction Network for Emotion Recognition in Conversations

no code implementations COLING 2020 Xin Lu, Yanyan Zhao, Yang Wu, Yijian Tian, Huipeng Chen, Bing Qin

We noticed that the gold emotion labels of the context utterances can provide explicit and accurate emotion interaction, but it is impossible to input gold labels at inference time.

Emotion Recognition in Conversation Natural Language Processing

Video Region Annotation with Sparse Bounding Boxes

no code implementations17 Aug 2020 Yuzheng Xu, Yang Wu, Nur Sabrina binti Zuraimi, Shohei Nobuhara, Ko Nishino

Video analysis has been moving towards more detailed interpretation (e. g. segmentation) with encouraging progresses.

Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

1 code implementation ECCV 2020 Jinlong Peng, Changan Wang, Fangbin Wan, Yang Wu, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yanwei Fu

Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or have two of the three subtasks integrated to form a partially end-to-end solution.

Multiple Object Tracking object-detection +1

When Person Re-identification Meets Changing Clothes

no code implementations9 Mar 2020 Fangbin Wan, Yang Wu, Xuelin Qian, Yixiong Chen, Yanwei Fu

We find that changing clothes makes ReID a much harder problem in the sense of bringing difficulties to learning effective representations and also challenges the generalization ability of previous ReID models to identify persons with unseen (new) clothes.

Person Re-Identification Person Search

Multiple Object Tracking by Flowing and Fusing

no code implementations30 Jan 2020 Jimuyang Zhang, Sanping Zhou, Xin Chang, Fangbin Wan, Jinjun Wang, Yang Wu, Dong Huang

Most of Multiple Object Tracking (MOT) approaches compute individual target features for two subtasks: estimating target-wise motions and conducting pair-wise Re-Identification (Re-ID).

Multiple Object Tracking object-detection +1

Compressing 3DCNNs Based on Tensor Train Decomposition

no code implementations8 Dec 2019 Dingheng Wang, Guangshe Zhao, Guoqi Li, Lei Deng, Yang Wu

However, due to the higher dimension of convolutional kernels, the space complexity of 3DCNNs is generally larger than that of traditional two dimensional convolutional neural networks (2DCNNs).

Hand Gesture Recognition Hand-Gesture Recognition +3

Using Panoramic Videos for Multi-person Localization and Tracking in a 3D Panoramic Coordinate

1 code implementation24 Nov 2019 Fan Yang, Feiran Li, Yang Wu, Sakriani Sakti, Satoshi Nakamura

3D panoramic multi-person localization and tracking are prominent in many applications, however, conventional methods using LiDAR equipment could be economically expensive and also computationally inefficient due to the processing of point cloud data.

 Ranked #1 on Multi-Object Tracking on MOT15_3D (using extra training data)

Multi-Object Tracking

Generalizing Energy-based Generative ConvNets from Particle Evolution Perspective

no code implementations31 Oct 2019 Yang Wu, Xu Cai, Pengxu Wei, Guanbin Li, Liang Lin

Compared with Generative Adversarial Networks (GAN), Energy-Based generative Models (EBMs) possess two appealing properties: i) they can be directly optimized without requiring an auxiliary network during the learning and synthesizing; ii) they can better approximate underlying distribution of the observed data by learning explicitly potential functions.

Make Skeleton-based Action Recognition Model Smaller, Faster and Better

3 code implementations arXiv 2019 Fan Yang, Sakriani Sakti, Yang Wu, Satoshi Nakamura

Although skeleton-based action recognition has achieved great success in recent years, most of the existing methods may suffer from a large model size and slow execution speed.

Action Recognition Skeleton Based Action Recognition

Dynamic Face Video Segmentation via Reinforcement Learning

no code implementations CVPR 2020 Yujiang Wang, Mingzhi Dong, Jie Shen, Yang Wu, Shiyang Cheng, Maja Pantic

To the best of our knowledge, this is the first work to use reinforcement learning for online key-frame decision in dynamic video segmentation, and also the first work on its application on face videos.

reinforcement-learning Video Segmentation +1

Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification

no code implementations24 May 2019 Zheng Wang, Zhixiang Wang, Yinqiang Zheng, Yang Wu, Wen-Jun Zeng, Shin'ichi Satoh

An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis.

Person Re-Identification

ReshapeGAN: Object Reshaping by Providing A Single Reference Image

1 code implementation16 May 2019 Ziqiang Zheng, Yang Wu, Zhibin Yu, Yang Yang, Haiyong Zheng, Takeo Kanade

We present the tailored models of the proposed ReshapeGAN for all the problem settings, and have them tested on 8 kinds of reshaping tasks with 13 different datasets, demonstrating the ability of ReshapeGAN on generating convincing and superior results for object reshaping.

Generative Adversarial Network with Multi-Branch Discriminator for Cross-Species Image-to-Image Translation

no code implementations24 Jan 2019 Ziqiang Zheng, Zhibin Yu, Haiyong Zheng, Yang Wu, Bing Zheng, Ping Lin

Current approaches have made great progress on image-to-image translation tasks benefiting from the success of image synthesis methods especially generative adversarial networks (GANs).

Image-to-Image Translation Translation

FRAME Revisited: An Interpretation View Based on Particle Evolution

no code implementations4 Dec 2018 Xu Cai, Yang Wu, Guanbin Li, Ziliang Chen, Liang Lin

FRAME (Filters, Random fields, And Maximum Entropy) is an energy-based descriptive model that synthesizes visual realism by capturing mutual patterns from structural input signals.

Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning

no code implementations ICLR 2018 Kunkun Pang, Mingzhi Dong, Yang Wu, Timothy Hospedales

In contrast to this body of research, we propose to treat active learning algorithm design as a meta-learning problem and learn the best criterion from data.

Active Learning Meta-Learning +1

Metric Learning via Maximizing the Lipschitz Margin Ratio

no code implementations9 Feb 2018 Mingzhi Dong, Xiaochen Yang, Yang Wu, Jing-Hao Xue

In this paper, we propose the Lipschitz margin ratio and a new metric learning framework for classification through maximizing the ratio.

Metric Learning

Pose-Normalized Image Generation for Person Re-identification

2 code implementations ECCV 2018 Xuelin Qian, Yanwei Fu, Tao Xiang, Wenxuan Wang, Jie Qiu, Yang Wu, Yu-Gang Jiang, xiangyang xue

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired training data and learning discriminative identity-sensitive and view-invariant features in the presence of large pose variations.

Image Generation Person Re-Identification +1

Saturation-Preserving Specular Reflection Separation

no code implementations CVPR 2015 Yuanliu Liu, Zejian yuan, Nanning Zheng, Yang Wu

Specular reflection generally decreases the saturation of surface colors, which will be possibly confused with other colors that have the same hue but lower saturation.

Collaborative Representation for Classification, Sparse or Non-sparse?

no code implementations6 Mar 2014 Yang Wu, Vansteenberge Jarich, Masayuki Mukunoki, Michihiko Minoh

Sparse representation based classification (SRC) has been proved to be a simple, effective and robust solution to face recognition.

Classification Dictionary Learning +3

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