134 citations · 920 across the 72 of their papers we have counts for
12 papers · 1 filter
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…