GaPT-DAR: Category-level Garments Pose Tracking via Integrated 2D Deformation and 3D Reconstruction

Li Zhang; Mingliang Xu; Jianan Wang; Qiaojun Yu; Lixin Yang; Yonglu Li; Cewu Lu; Rujing Wang; Liu Liu

doi:10.1109/cvpr52734.2025.02108

CVPR2025顶会

GaPT-DAR: Category-level Garments Pose Tracking via Integrated 2D Deformation and 3D Reconstruction

Li Zhang, Mingliang Xu, Jianan Wang, Qiaojun Yu, Lixin Yang, Yonglu Li, Cewu Lu, Rujing Wang, Liu Liu

DOI 出版方

2025年份

2顶会引用

摘要

Figure 1. Category-level Garments Pose Tracking framework with integrated 2D Deformation And 3D Reconstruction (GaPT-DAR). Given the partial point clouds from adjacent frames and pose prediction result from the previous frame, we propose a garment pose tracking pipeline consisting of 3D-2D projection, 2D deformation learning, and 2D-3D reconstruction steps. The output is the tracked pose (complete point cloud) of garments in task space.