25 citations · 28 across the 5 of their papers we have counts for
5 papers
Deep Learning Technique for Human Parsing: A Survey and Outlook
Lu Yang, Wenhe Jia, Shan Li +1
Human parsing aims to partition humans in image or video into multiple pixel-level semantic parts. In the last decade, it has gained significantly increased interest in the compute…
UV R-CNN: Stable and Efficient Dense Human Pose Estimation
Wenhe Jia, Yilin Zhou, Xuhan Zhu +3
Dense pose estimation is a dense 3D prediction task for instance-level human analysis, aiming to map human pixels from an RGB image to a 3D surface of the human body. Due to a larg…
TIVE: A Toolbox for Identifying Video Instance Segmentation Errors
Wenhe Jia, Lu Yang, Zilong Jia +3
Since first proposed, Video Instance Segmentation(VIS) task has attracted vast researchers' focus on architecture modeling to boost performance. Though great advances achieved in o…
Quality-Aware Network for Face Parsing
Lu Yang, Qing Song, Xueshi Xin +2
This is a very short technical report, which introduces the solution of the Team BUPT-CASIA for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Chall…
Renovating Parsing R-CNN for Accurate Multiple Human Parsing
Lu Yang, Qing Song, Zhihui Wang +5
Multiple human parsing aims to segment various human parts and associate each part with the corresponding instance simultaneously. This is a very challenging task due to the divers…