4D-DRESS: A 4D Dataset of Real-World Human Clothing with Semantic Annotations

Wenbo Wang; Hsuan-I Ho; Chen Guo; Boxiang Rong; Artur Grigorev; Jie Song; Juan Jose Zarate; Otmar Hilliges

doi:10.1109/cvpr52733.2024.00059

CVPR2024顶会

4D-DRESS: A 4D Dataset of Real-World Human Clothing with Semantic Annotations

Wenbo Wang, Hsuan-I Ho, Chen Guo, Boxiang Rong, Artur Grigorev, Jie Song, Juan Jose Zarate, Otmar Hilliges

DOI 出版方

2024年份

5顶会引用

摘要

https://ait.ethz.ch/4d-dress Figure 1 . Overview of 4D-DRESS. We propose the first real-world 4D dataset of human clothing, capturing 64 human outfits in more than 520 motion sequences. These sequences include a) high-quality 4D textured scans; for each scan, we annotate b) vertex-level semantic labels, thereby obtaining c) the corresponding garment meshes and fitted SMPL(-X) body meshes.