Dress-Me-Up: A Dataset & Method for Self-Supervised 3D Garment Retargeting

• URL: http://arxiv.org/abs/2401.03108v1
• Date: Sat, 6 Jan 2024 02:28:25 GMT
• Title: Dress-Me-Up: A Dataset & Method for Self-Supervised 3D Garment Retargeting
• Authors: Shanthika Naik, Kunwar Singh, Astitva Srivastava, Dhawal Sirikonda, Amit Raj, Varun Jampani, Avinash Sharma
• Abstract summary: We propose a novel framework for non-parametricized 3D garments onto 3D human avatars of arbitrary shapes and poses. Existing self-supervised 3D methods only support parametric and canonical garments. We show superior quality on non-supervised garments and human avatars over existing state-of-the-art methods.
• Score: 28.892029042436626
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We propose a novel self-supervised framework for retargeting non-parameterized 3D garments onto 3D human avatars of arbitrary shapes and poses, enabling 3D virtual try-on (VTON). Existing self-supervised 3D retargeting methods only support parametric and canonical garments, which can only be draped over parametric body, e.g. SMPL. To facilitate the non-parametric garments and body, we propose a novel method that introduces Isomap Embedding based correspondences matching between the garment and the human body to get a coarse alignment between the two meshes. We perform neural refinement of the coarse alignment in a self-supervised setting. Further, we leverage a Laplacian detail integration method for preserving the inherent details of the input garment. For evaluating our 3D non-parametric garment retargeting framework, we propose a dataset of 255 real-world garments with realistic noise and topological deformations. The dataset contains $44$ unique garments worn by 15 different subjects in 5 distinctive poses, captured using a multi-view RGBD capture setup. We show superior retargeting quality on non-parametric garments and human avatars over existing state-of-the-art methods, acting as the first-ever baseline on the proposed dataset for non-parametric 3D garment retargeting.

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