ClothCombo: Modeling Inter-Cloth Interaction for Draping Multi-Layered
Clothes
- URL: http://arxiv.org/abs/2304.03492v2
- Date: Thu, 30 Nov 2023 14:00:56 GMT
- Title: ClothCombo: Modeling Inter-Cloth Interaction for Draping Multi-Layered
Clothes
- Authors: Dohae Lee, Hyun Kang, In-Kwon Lee
- Abstract summary: We present ClothCombo, a pipeline to drape arbitrary combinations of clothes on 3D human models.
Our method utilizes a GNN-based network to efficiently model the interaction between clothes in different layers.
- Score: 3.8079353598215757
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: We present ClothCombo, a pipeline to drape arbitrary combinations of clothes
on 3D human models with varying body shapes and poses. While existing
learning-based approaches for draping clothes have shown promising results,
multi-layered clothing remains challenging as it is non-trivial to model
inter-cloth interaction. To this end, our method utilizes a GNN-based network
to efficiently model the interaction between clothes in different layers, thus
enabling multi-layered clothing. Specifically, we first create feature
embedding for each cloth using a topology-agnostic network. Then, the draping
network deforms all clothes to fit the target body shape and pose without
considering inter-cloth interaction. Lastly, the untangling network predicts
the per-vertex displacements in a way that resolves interpenetration between
clothes. In experiments, the proposed model demonstrates strong performance in
complex multi-layered scenarios. Being agnostic to cloth topology, our method
can be readily used for layered virtual try-on of real clothes in diverse poses
and combinations of clothes.
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