98 citations · 675 across the 50 of their papers we have counts for
4 papers · 1 filter
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
Zhenyi Wang, Ping Yu, Yang Zhao +4
Human-motion generation is a long-standing challenging task due to the requirement of accurately modeling complex and diverse dynamic patterns. Most existing methods adopt sequence…
A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image
Fu Xiong, Boshen Zhang, Yang Xiao +4
For 3D hand and body pose estimation task in depth image, a novel anchor-based approach termed Anchor-to-Joint regression network (A2J) with the end-to-end learning ability is prop…
Context-Integrated and Feature-Refined Network for Lightweight Object Parsing
Bin Jiang, Wenxuan Tu, Chao Yang +1
Semantic segmentation for lightweight object parsing is a very challenging task, because both accuracy and efficiency (e.g., execution speed, memory footprint or computational comp…
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation
Jun Wen, Nenggan Zheng, Junsong Yuan +2
Domain adaptation is an important technique to alleviate performance degradation caused by domain shift, e.g., when training and test data come from different domains. Most existin…