CVPR 2023 – Learning Anchor Transformations for 3D Garment Animation

In this episode we discuss Learning Anchor Transformations for 3D Garment Animation
by Fang Zhao, Zekun Li, Shaoli Huang, Junwu Weng, Tianfei Zhou, Guo-Sen Xie, Jue Wang, Ying Shan. The paper presents a new anchor-based deformation model called AnchorDEF, which predicts 3D garment animation from a body motion sequence. The model deforms a garment mesh template using a mixture of rigid transformations and extra nonlinear displacements, guided by a set of anchors around the mesh surface. The transformed anchors are constrained to satisfy position, normal, and direction consistencies, ensuring better generalization. The model achieves state-of-the-art performance on 3D garment deformation prediction, especially for loose-fitting garments.