29 citations · 58 across the 9 of their papers we have counts for
9 papers
ORTexME: Occlusion-Robust Human Shape and Pose via Temporal Average Texture and Mesh Encoding
Yu Cheng, Bo Wang, Robby T. Tan
In 3D human shape and pose estimation from a monocular video, models trained with limited labeled data cannot generalize well to videos with occlusion, which is common in the wild…
DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment
Heyuan Li, Bo Wang, Yu Cheng +2
Sensitivity to severe occlusion and large view angles limits the usage scenarios of the existing monocular 3D dense face alignment methods. The state-of-the-art 3DMM-based method,…
Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimation
Han Li, Bowen Shi, Wenrui Dai +7
There has been a recent surge of interest in introducing transformers to 3D human pose estimation (HPE) due to their powerful capabilities in modeling long-term dependencies. Howev…
Bottom-Up 2D Pose Estimation via Dual Anatomical Centers for Small-Scale Persons
Yu Cheng, Yihao Ai, Bo Wang +2
In multi-person 2D pose estimation, the bottom-up methods simultaneously predict poses for all persons, and unlike the top-down methods, do not rely on human detection. However, th…
Dual networks based 3D Multi-Person Pose Estimation from Monocular Video
Yu Cheng, Bo Wang, Robby T. Tan
Monocular 3D human pose estimation has made progress in recent years. Most of the methods focus on single persons, which estimate the poses in the person-centric coordinates, i.e.,…
Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
Yu Cheng, Bo Wang, Bo Yang +1
In monocular video 3D multi-person pose estimation, inter-person occlusion and close interactions can cause human detection to be erroneous and human-joints grouping to be unreliab…