作者
Ce Zheng, Matias Mendieta, Pu Wang, Aidong Lu, Chen Chen
发表日期
2022/10/10
图书
Proceedings of the 30th ACM international conference on multimedia
页码范围
5496-5507
简介
Existing deep learning-based human mesh reconstruction approaches have a tendency to build larger networks to achieve higher accuracy. Computational complexity and model size are often neglected, despite being key characteristics for practical use of human mesh reconstruction models (e.g. virtual try-on systems). In this paper, we present GTRS, a lightweight pose-based method that can reconstruct human mesh from 2D human pose. We propose a pose analysis module that uses graph transformers to exploit structured and implicit joint correlations, and a mesh regression module that combines the extracted pose feature with the mesh template to reconstruct the final human mesh. We demonstrate the efficiency and generalization of GTRS by extensive evaluations on the Human3.6M and 3DPW datasets. In particular, GTRS achieves better accuracy than the SOTA pose-based method Pose2Mesh while only …
引用总数
学术搜索中的文章
C Zheng, M Mendieta, P Wang, A Lu, C Chen - Proceedings of the 30th ACM international conference …, 2022