GIM3D: A 3D Dataset for Garment Segmentation
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
The 3D cloth segmentation task is particularly challenging due to the extreme variation of shapes, even among the same category of clothes. Several data-driven methods try to cope with this problem but they have to face the lack of available data capable to generalize to the variety of real-world data. For this reason, we present GIM3D (Garments In Motion 3D), a synthetic dataset of clothed 3D human characters in different poses. The over 4000 3D models in this dataset are produced by a physical simulation of clothes with different fabrics, sizes, and tightness, using animated human avatars having a large variety of shapes. Our dataset is composed of single meshes created to simulate 3D scans, with labels for the separate clothes and the visible body parts. We also provide an evaluation of the use of GIM3D as a training set on garment segmentation tasks using state-of-the-art data-driven methods for both meshes and point clouds.
Description
CCS Concepts: Computing methodologies -> Shape analysis; Theory of computation -> Computational geometry; Mathematics of computing -> Functional analysis
@inproceedings{10.2312:stag.20221252,
booktitle = {Smart Tools and Applications in Graphics - Eurographics Italian Chapter Conference},
editor = {Cabiddu, Daniela and Schneider, Teseo and Allegra, Dario and Catalano, Chiara Eva and Cherchi, Gianmarco and Scateni, Riccardo},
title = {{GIM3D: A 3D Dataset for Garment Segmentation}},
author = {Musoni, Pietro and Melzi, Simone and Castellani, Umberto},
year = {2022},
publisher = {The Eurographics Association},
ISSN = {2617-4855},
ISBN = {978-3-03868-191-5},
DOI = {10.2312/stag.20221252}
}