471 citations · 2.8k across the 50 of their papers we have counts for
31 papers · 1 filter
Part-level Action Parsing via a Pose-guided Coarse-to-Fine Framework
Xiaodong Chen, Xinchen Liu, Wu Liu +4
Action recognition from videos, i.e., classifying a video into one of the pre-defined action types, has been a popular topic in the communities of artificial intelligence, multimed…
From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network
Yuxin Wang, Hongtao Xie, Shancheng Fang +3
In this paper, we abandon the dominant complex language model and rethink the linguistic learning process in the scene text recognition. Different from previous methods considering…
Cross-Modal Attention Consistency for Video-Audio Unsupervised Learning
Shaobo Min, Qi Dai, Hongtao Xie +3
Cross-modal correlation provides an inherent supervision for video unsupervised representation learning. Existing methods focus on distinguishing different video clips by visual an…
Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
Yulin Li, Jianfeng He, Tianzhu Zhang +3
Occluded person re-identification (Re-ID) is a challenging task as persons are frequently occluded by various obstacles or other persons, especially in the crowd scenario. To addre…
PERT: A Progressively Region-based Network for Scene Text Removal
Yuxin Wang, Hongtao Xie, Shancheng Fang +2
Scene text removal (STR) contains two processes: text localization and background reconstruction. Through integrating both processes into a single network, previous methods provide…
Action Unit Memory Network for Weakly Supervised Temporal Action Localization
Wang Luo, Tianzhu Zhang, Wenfei Yang +4
Weakly supervised temporal action localization aims to detect and localize actions in untrimmed videos with only video-level labels during training. However, without frame-level an…
Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection
Jiaming Li, Hongtao Xie, Jiahong Li +2
Face forgery detection is raising ever-increasing interest in computer vision since facial manipulation technologies cause serious worries. Though recent works have reached sound a…
Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition
Shancheng Fang, Hongtao Xie, Yuxin Wang +2
Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively model linguistic rules in end-to-end deep networks remains a research challenge. In…
Explainable Person Re-Identification with Attribute-guided Metric Distillation
Xiaodong Chen, Xinchen Liu, Wu Liu +3
Despite the great progress of person re-identification (ReID) with the adoption of Convolutional Neural Networks, current ReID models are opaque and only outputs a scalar distance…
Overcoming Language Priors with Self-supervised Learning for Visual Question Answering
Xi Zhu, Zhendong Mao, Chunxiao Liu +3
Most Visual Question Answering (VQA) models suffer from the language prior problem, which is caused by inherent data biases. Specifically, VQA models tend to answer questions (e.g.…
Attribute-Induced Bias Eliminating for Transductive Zero-Shot Learning
Hantao Yao, Shaobo Min, Yongdong Zhang +1
Transductive Zero-shot learning (ZSL) targets to recognize the unseen categories by aligning the visual and semantic information in a joint embedding space. There exist four kinds…
ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection
Yuxin Wang, Hongtao Xie, Zhengjun Zha +3
Scene text detection has witnessed rapid development in recent years. However, there still exists two main challenges: 1) many methods suffer from false positives in their text rep…
Multi-Objective Matrix Normalization for Fine-grained Visual Recognition
Shaobo Min, Hantao Yao, Hongtao Xie +2
Bilinear pooling achieves great success in fine-grained visual recognition (FGVC). Recent methods have shown that the matrix power normalization can stabilize the second-order info…
Domain-aware Visual Bias Eliminating for Generalized Zero-Shot Learning
Shaobo Min, Hantao Yao, Hongtao Xie +3
Recent methods focus on learning a unified semantic-aligned visual representation to transfer knowledge between two domains, while ignoring the effect of semantic-free visual repre…
Graph Structured Network for Image-Text Matching
Chunxiao Liu, Zhendong Mao, Tianzhu Zhang +3
Image-text matching has received growing interest since it bridges vision and language. The key challenge lies in how to learn correspondence between image and text. Existing works…
Asymmetric GAN for Unpaired Image-to-image Translation
Yu Li, Sheng Tang, Rui Zhang +3
Unpaired image-to-image translation problem aims to model the mapping from one domain to another with unpaired training data. Current works like the well-acknowledged Cycle GAN pro…
ACE-Net: Biomedical Image Segmentation with Augmented Contracting and Expansive Paths
Yanhao Zhu, Zhineng Chen, Shuai Zhao +3
Nowadays U-net-like FCNs predominate various biomedical image segmentation applications and attain promising performance, largely due to their elegant architectures, e.g., symmetri…
Domain-Specific Embedding Network for Zero-Shot Recognition
Shaobo Min, Hantao Yao, Hongtao Xie +2
Zero-Shot Learning (ZSL) seeks to recognize a sample from either seen or unseen domain by projecting the image data and semantic labels into a joint embedding space. However, most…
Consensus Feature Network for Scene Parsing
Tianyi Wu, Sheng Tang, Rui Zhang +2
Scene parsing is challenging as it aims to assign one of the semantic categories to each pixel in scene images. Thus, pixel-level features are desired for scene parsing. However, c…
Dense Scale Network for Crowd Counting
Feng Dai, Hao Liu, Yike Ma +3
Crowd counting has been widely studied by computer vision community in recent years. Due to the large scale variation, it remains to be a challenging task. Previous methods adopt e…
Context-Aware Visual Policy Network for Fine-Grained Image Captioning
Zheng-Jun Zha, Daqing Liu, Hanwang Zhang +2
With the maturity of visual detection techniques, we are more ambitious in describing visual content with open-vocabulary, fine-grained and free-form language, i.e., the task of im…
Not All Words are Equal: Video-specific Information Loss for Video Captioning
Jiarong Dong, Ke Gao, Xiaokai Chen +3
An ideal description for a given video should fix its gaze on salient and representative content, which is capable of distinguishing this video from others. However, the distributi…
CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification
Jiawei Liu, Zheng-Jun Zha, Hongtao Xie +2
Person re-identification aims to identify the same pedestrian across non-overlapping camera views. Deep learning techniques have been applied for person re-identification recently,…
Style Separation and Synthesis via Generative Adversarial Networks
Rui Zhang, Sheng Tang, Yu Li +4
Style synthesis attracts great interests recently, while few works focus on its dual problem "style separation". In this paper, we propose the Style Separation and Synthesis Genera…