1 code implementation • CVPR 2023 • Changlong Jiang, Yang Xiao, Cunlin Wu, Mingyang Zhang, Jinghong Zheng, Zhiguo Cao, Joey Tianyi Zhou
3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance patterns between 2 hands, ill-posed joint position mapping from 2D to 3D, etc.. To address these, we propose to extend A2J-the state-of-the-art depth-based 3D single hand pose estimation method-to RGB domain under interacting hand condition.
Ranked #7 on Hand Pose Estimation on NYU Hands
no code implementations • 23 Aug 2022 • Boshen Zhang, Yuxi Li, Yuanpeng Tu, Jinlong Peng, Yabiao Wang, Cunlin Wu, Yang Xiao, Cairong Zhao
Specifically, for the clean set, we deliberately design a memory-based modulation scheme to dynamically adjust the contribution of each sample in terms of its historical credibility sequence during training, thus alleviating the effect from noisy samples incorrectly grouped into the clean set.