Title
Learning 3D Human Shape and Pose From Dense Body Parts
Abstract
Reconstructing 3D human shape and pose from monocular images is challenging despite the promising results achieved by the most recent learning-based methods. The commonly occurred misalignment comes from the facts that the mapping from images to the model space is highly non-linear and the rotation-based pose representation of the body model is prone to result in the drift of joint positions. In t...
Year
DOI
Venue
2022
10.1109/TPAMI.2020.3042341
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keywords
DocType
Volume
Three-dimensional displays,Shape,Task analysis,Solid modeling,Two dimensional displays,Predictive models,Pose estimation
Journal
44
Issue
ISSN
Citations 
5
0162-8828
1
PageRank 
References 
Authors
0.34
37
5
Name
Order
Citations
PageRank
Hongwen Zhang1132.61
Jie Cao262773.36
Guo Lu3258.02
Wanli Ouyang42371105.17
Zhenan Sun52379139.49