GarmentTracking: Category-Level Garment Pose Tracking 

Abstract: Garments are important to humans. A visual system that can estimate and track the complete garment pose can be useful for many downstream tasks and real-world applications. In this work, we present a complete package to address the category-level garment pose tracking task: (1) A recording system VR-Garment, with which users can manipulate virtual garment models in simulation through a VR interface. (2) A large-scale dataset VR-Folding, with complex garment pose configurations in manipulation like flattening and folding. (3) An end-to-end online tracking framework GarmentTracking, which predicts complete garment pose both in canonical space and task space given a point cloud sequence. Extensive experiments demonstrate that the proposed GarmentTracking achieves great performance even when the garment has large non-rigid deformation. It outperforms the baseline approach on both speed and accuracy. We hope our proposed solution can serve as a platform for future research.

Summary Video: youtube 

Code: https://github.com/xiaoxiaoxh/GarmentTracking

Dataset: here 

VR-Garment Recording System: https://github.com/xiaoxiaoxh/VR-Garment

Paper: arXiv

Poster: here 

Shirt Flattening

Pants Flattening

Top Flattening

Skirt Flattening

Shirt Folding

Pants Folding

Top Folding

Skirt Folding