252 citations · 472 across the 19 of their papers we have counts for
19 papers
Joint-Motion Mutual Learning for Pose Estimation in Videos
Sifan Wu, Haipeng Chen, Yifang Yin +5
Human pose estimation in videos has long been a compelling yet challenging task within the realm of computer vision. Nevertheless, this task remains difficult because of the comple…
Alleviating Structural Distribution Shift in Graph Anomaly Detection
Yuan Gao, Xiang Wang, Xiangnan He +3
Graph anomaly detection (GAD) is a challenging binary classification problem due to its different structural distribution between anomalies and normal nodes -- abnormal nodes are a…
Prototypical Cross-domain Knowledge Transfer for Cervical Dysplasia Visual Inspection
Yichen Zhang, Yifang Yin, Ying Zhang +3
Early detection of dysplasia of the cervix is critical for cervical cancer treatment. However, automatic cervical dysplasia diagnosis via visual inspection, which is more appropria…
Action Recognition with Multi-stream Motion Modeling and Mutual Information Maximization
Yuheng Yang, Haipeng Chen, Zhenguang Liu +5
Action recognition has long been a fundamental and intriguing problem in artificial intelligence. The task is challenging due to the high dimensionality nature of an action, as wel…
TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
Yuwei Yin, Jean Kaddour, Xiang Zhang +4
Data augmentation has been established as an efficacious approach to supplement useful information for low-resource datasets. Traditional augmentation techniques such as noise inje…
Copy Motion From One to Another: Fake Motion Video Generation
Zhenguang Liu, Sifan Wu, Chejian Xu +4
One compelling application of artificial intelligence is to generate a video of a target person performing arbitrary desired motion (from a source person). While the state-of-the-a…
2D Human Pose Estimation: A Survey
Haoming Chen, Runyang Feng, Sifan Wu +3
Human pose estimation aims at localizing human anatomical keypoints or body parts in the input data (e.g., images, videos, or signals). It forms a crucial component in enabling mac…
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings
Yuhao Mao, Chong Fu, Saizhuo Wang +7
One intriguing property of adversarial attacks is their "transferability" -- an adversarial example crafted with respect to one deep neural network (DNN) model is often found effec…
Temporal Feature Alignment and Mutual Information Maximization for Video-Based Human Pose Estimation
Zhenguang Liu, Runyang Feng, Haoming Chen +4
Multi-frame human pose estimation has long been a compelling and fundamental problem in computer vision. This task is challenging due to fast motion and pose occlusion that frequen…
3D Human Motion Prediction: A Survey
Kedi Lyu, Haipeng Chen, Zhenguang Liu +2
3D human motion prediction, predicting future poses from a given sequence, is an issue of great significance and challenge in computer vision and machine intelligence, which can he…
Dual Learning Music Composition and Dance Choreography
Shuang Wu, Zhenguang Li, Shijian Lu +1
Music and dance have always co-existed as pillars of human activities, contributing immensely to the cultural, social, and entertainment functions in virtually all societies. Notwi…
Motion Prediction via Joint Dependency Modeling in Phase Space
Pengxiang Su, Zhenguang Liu, Shuang Wu +3
Motion prediction is a classic problem in computer vision, which aims at forecasting future motion given the observed pose sequence. Various deep learning models have been proposed…
Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction
Zhenguang Liu, Shuang Wu, Shuyuan Jin +4
Predicting human motion from historical pose sequence is crucial for a machine to succeed in intelligent interactions with humans. One aspect that has been obviated so far, is the…
Learning Human Motion Prediction via Stochastic Differential Equations
Kedi Lyu, Zhenguang Liu, Shuang Wu +3
Human motion understanding and prediction is an integral aspect in our pursuit of machine intelligence and human-machine interaction systems. Current methods typically pursue a kin…
Parallel Multi-Graph Convolution Network For Metro Passenger Volume Prediction
Fuchen Gao, Zhanquan Wang, Zhenguang Liu
Accurate prediction of metro passenger volume (number of passengers) is valuable to realize real-time metro system management, which is a pivotal yet challenging task in intelligen…
Exploring Lottery Ticket Hypothesis in Media Recommender Systems
Yanfang Wang, Yongduo Sui, Xiang Wang +2
Media recommender systems aim to capture users' preferences and provide precise personalized recommendation of media content. There are two critical components in the common paradi…
Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection
Zhenguang Liu, Peng Qian, Xiaoyang Wang +3
Smart contract vulnerability detection draws extensive attention in recent years due to the substantial losses caused by hacker attacks. Existing efforts for contract security anal…
Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion
Zhenguang Liu, Peng Qian, Xiang Wang +3
Smart contracts hold digital coins worth billions of dollars, their security issues have drawn extensive attention in the past years. Towards smart contract vulnerability detection…
Aggregated Multi-GANs for Controlled 3D Human Motion Prediction
Zhenguang Liu, Kedi Lyu, Shuang Wu +3
Human motion prediction from historical pose sequence is at the core of many applications in machine intelligence. However, in current state-of-the-art methods, the predicted futur…