471 citations · 2.8k across the 50 of their papers we have counts for
50 papers
Rumor Detection with Self-supervised Learning on Texts and Social Graph
Yuan Gao, Xiang Wang, Xiangnan He +2
Rumor detection has become an emerging and active research field in recent years. At the core is to model the rumor characteristics inherent in rich information, such as propagatio…
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…
Causal Incremental Graph Convolution for Recommender System Retraining
Sihao Ding, Fuli Feng, Xiangnan He +3
Real-world recommender system needs to be regularly retrained to keep with the new data. In this work, we consider how to efficiently retrain graph convolution network (GCN) based…
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…
Causal Intervention for Leveraging Popularity Bias in Recommendation
Yang Zhang, Fuli Feng, Xiangnan He +4
Recommender system usually faces popularity bias issues: from the data perspective, items exhibit uneven (long-tail) distribution on the interaction frequency; from the method pers…
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.…
Reliability Enhancement for VR Delivery in Mobile-Edge Empowered Dual-Connectivity Sub-6 GHz and mmWave HetNets
Zhuojia Gu, Hancheng Lu, Peilin Hong +1
The reliability of current virtual reality (VR) delivery is low due to the limited resources on VR head-mounted displays (HMDs) and the transmission rate bottleneck of sub-6 GHz ne…
CatGCN: Graph Convolutional Networks with Categorical Node Features
Weijian Chen, Fuli Feng, Qifan Wang +4
Recent studies on Graph Convolutional Networks (GCNs) reveal that the initial node representations (i.e., the node representations before the first-time graph convolution) largely…
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…
Bilinear Graph Neural Network with Neighbor Interactions
Hongmin Zhu, Fuli Feng, Xiangnan He +4
Graph Neural Network (GNN) is a powerful model to learn representations and make predictions on graph data. Existing efforts on GNN have largely defined the graph convolution as a…
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He, Kuan Deng, Xiang Wang +3
Graph Convolution Network (GCN) has become new state-of-the-art for collaborative filtering. Nevertheless, the reasons of its effectiveness for recommendation are not well understo…
Graph Convolution Machine for Context-aware Recommender System
Jiancan Wu, Xiangnan He, Xiang Wang +4
The latest advance in recommendation shows that better user and item representations can be learned via performing graph convolutions on the user-item interaction graph. However, s…
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…