134 citations · 920 across the 72 of their papers we have counts for
72 papers
3D Human Mesh Estimation from Virtual Markers
Xiaoxuan Ma, Jiajun Su, Chunyu Wang +2
Inspired by the success of volumetric 3D pose estimation, some recent human mesh estimators propose to estimate 3D skeletons as intermediate representations, from which, the dense…
Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection
Hang Ye, Wentao Zhu, Chunyu Wang +2
While the voxel-based methods have achieved promising results for multi-person 3D pose estimation from multi-cameras, they suffer from heavy computation burdens, especially for lar…
VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual Data
Jiajun Su, Chunyu Wang, Xiaoxuan Ma +2
While monocular 3D pose estimation seems to have achieved very accurate results on the public datasets, their generalization ability is largely overlooked. In this work, we perform…
Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains
Haiyang Yang, Meilin Chen, Yizhou Wang +5
Generalizing learned representations across significantly different visual domains is a fundamental yet crucial ability of the human visual system. While recent self-supervised lea…
Domain Invariant Model with Graph Convolutional Network for Mammogram Classification
Churan Wang, Jing Li, Xinwei Sun +3
Due to its safety-critical property, the image-based diagnosis is desired to achieve robustness on out-of-distribution (OOD) samples. A natural way towards this goal is capturing o…
Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition
Yingjie Chen, Diqi Chen, Tao Wang +2
Subject-invariant facial action unit (AU) recognition remains challenging for the reason that the data distribution varies among subjects. In this paper, we propose a causal infere…
GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning
Tianhao Wu, Fangwei Zhong, Yiran Geng +4
Grasping moving objects, such as goods on a belt or living animals, is an important but challenging task in robotics. Conventional approaches rely on a set of manually defined obje…
EventFormer: AU Event Transformer for Facial Action Unit Event Detection
Yingjie Chen, Jiarui Zhang, Tao Wang +1
Facial action units (AUs) play an indispensable role in human emotion analysis. We observe that although AU-based high-level emotion analysis is urgently needed by real-world appli…
MoCaNet: Motion Retargeting in-the-wild via Canonicalization Networks
Wentao Zhu, Zhuoqian Yang, Ziang Di +3
We present a novel framework that brings the 3D motion retargeting task from controlled environments to in-the-wild scenarios. In particular, our method is capable of retargeting b…
Revisiting the Transferability of Supervised Pretraining: an MLP Perspective
Yizhou Wang, Shixiang Tang, Feng Zhu +4
The pretrain-finetune paradigm is a classical pipeline in visual learning. Recent progress on unsupervised pretraining methods shows superior transfer performance to their supervis…
SLAP: Self-supervised Anomaly Detection with Adversarial Perturbation
Yizhou Wang, Can Qin, Rongzhe Wei +3
Anomaly detection is a fundamental yet challenging problem in machine learning due to the lack of label information. In this work, we propose a novel and powerful framework, dubbed…
ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind
Yuanfei Wang, Fangwei Zhong, Jing Xu +1
Being able to predict the mental states of others is a key factor to effective social interaction. It is also crucial for distributed multi-agent systems, where agents are required…
Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images
Kongming Liang, Kai Han, Xiuli Li +4
Quantitative estimation of the acute ischemic infarct is crucial to improve neurological outcomes of the patients with stroke symptoms. Since the density of lesions is subtle and c…
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition
Mingzhou Liu, Xinwei Sun, Fandong Zhang +2
Context, as referred to situational factors related to the object of interest, can help infer the object's states or properties in visual recognition. As such contextual features a…
Towards Distraction-Robust Active Visual Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo +2
In active visual tracking, it is notoriously difficult when distracting objects appear, as distractors often mislead the tracker by occluding the target or bringing a confusing app…
Towards Unified Surgical Skill Assessment
Daochang Liu, Qiyue Li, Tingting Jiang +4
Surgical skills have a great influence on surgical safety and patients' well-being. Traditional assessment of surgical skills involves strenuous manual efforts, which lacks efficie…
Rethinking Adam: A Twofold Exponential Moving Average Approach
Yizhou Wang, Yue Kang, Can Qin +4
Adaptive gradient methods, e.g. \textsc{Adam}, have achieved tremendous success in machine learning. Scaling the learning rate element-wisely by a certain form of second moment est…
Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection
Yuhang Liu, Fandong Zhang, Chaoqi Chen +3
Mammogram mass detection is crucial for diagnosing and preventing the breast cancers in clinical practice. The complementary effect of multi-view mammogram images provides valuable…
Causal Hidden Markov Model for Time Series Disease Forecasting
Jing Li, Botong Wu, Xinwei Sun +1
We propose a causal hidden Markov model to achieve robust prediction of irreversible disease at an early stage, which is safety-critical and vital for medical treatment in early st…
Context Modeling in 3D Human Pose Estimation: A Unified Perspective
Xiaoxuan Ma, Jiajun Su, Chunyu Wang +2
Estimating 3D human pose from a single image suffers from severe ambiguity since multiple 3D joint configurations may have the same 2D projection. The state-of-the-art methods ofte…
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
Shu Zhang, Jincheng Xu, Yu-Chun Chen +4
Universal lesion detection from computed tomography (CT) slices is important for comprehensive disease screening. Since each lesion can locate in multiple adjacent slices, 3D conte…
Forecasting Irreversible Disease via Progression Learning
Botong Wu, Sijie Ren, Jing Li +3
Forecasting Parapapillary atrophy (PPA), i.e., a symptom related to most irreversible eye diseases, provides an alarm for implementing an intervention to slow down the disease prog…
An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation
Rongchang Xie, Chunyu Wang, Wenjun Zeng +1
Semi-supervised learning aims to boost the accuracy of a model by exploring unlabeled images. The state-of-the-art methods are consistency-based which learn about unlabeled images…
Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks
Jing Xu, Fangwei Zhong, Yizhou Wang
Maximum target coverage by adjusting the orientation of distributed sensors is an important problem in directional sensor networks (DSNs). This problem is challenging as the target…