activity
20142026
most citedUnsupervised Learning of Visual Representations using Videos

195 citations · 1.4k across the 56 of their papers we have counts for

collaborators
Showing 2020Show all

8 papers · 1 filter

cs.CV2020★ 19 cited

Online Adaptation for Consistent Mesh Reconstruction in the Wild

Xueting Li, Sifei Liu, Shalini De Mello +4

This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild. Without requiring annotations of 3D mesh, 2D…

cs.CV2020★ 6 cited

Synthesizing Long-Term 3D Human Motion and Interaction in 3D Scenes

Jiashun Wang, Huazhe Xu, Jingwei Xu +2

Synthesizing 3D human motion plays an important role in many graphics applications as well as understanding human activity. While many efforts have been made on generating realisti…

cs.CV2020

Adaptive Compact Attention For Few-shot Video-to-video Translation

Risheng Huang, Li Shen, Xuan Wang +2

This paper proposes an adaptive compact attention model for few-shot video-to-video translation. Existing works in this domain only use features from pixel-wise attention without c…

cs.CV2020★ 11 cited

Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction

Xuanzhao Wang, Zhengping Che, Bo Jiang +6

Video anomaly detection is commonly used in many applications such as security surveillance and is very challenging.A majority of recent video anomaly detection approaches utilize…

cs.LG2020

Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection

Chunkai Zhang, Wei Zuo, Xuan Wang

Anomaly detection in time series has been widely researched and has important practical applications. In recent years, anomaly detection algorithms are mostly based on deep-learnin…

cs.LG2020

RLCFR: Minimize Counterfactual Regret by Deep Reinforcement Learning

Huale Li, Xuan Wang, Fengwei Jia +4

Counterfactual regret minimization (CFR) is a popular method to deal with decision-making problems of two-player zero-sum games with imperfect information. Unlike existing studies…