Hybrid Retrieval-Regression for Motion-Driven Loose-Fitting Garment Animation
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We present a hybrid retrieval-regression framework for motion-driven garment animation leveraging a shared discrete codebook. Our method targets the challenge of animating loose-fitting garments, whose dynamic behaviors exhibit high variability and less direct correlation with body motion-making them difficult to handle with conventional example-based approaches that assume tightly coupled motion-garment relationships. To address this, we project both motion and garment animation clips into a shared discrete codebook via Gumbel-Softmax-based quantization, allowing them to be aligned in a semantically consistent space where cross-retrieval can be performed using simple distance metrics. During inference, we adaptively switch between retrieval and regression based on the confidence derived from the codebook probability distribution, allowing the system to remain robust in the presence of ambiguous or unseen motions. We leverage a pre-trained mesh autoencoder to obtain garment latents that preserve local geometric structure, enabling smoother transitions and more geometrically consistent interpolation between retrieved and regressed animation segments efficiently. Experimental results demonstrate that our approach improves the accuracy and plausibility of garment animation for complex garments under diverse motion inputs, while maintaining robustness to unseen scenarios and achieving low simulation error for high-quality garment animation.
Description
CCS Concepts: Computing methodologies → Animation; Learning latent representations; Discrete space search
@inproceedings{10.2312:pg.20251259,
booktitle = {Pacific Graphics Conference Papers, Posters, and Demos},
editor = {Christie, Marc and Han, Ping-Hsuan and Lin, Shih-Syun and Pietroni, Nico and Schneider, Teseo and Tsai, Hsin-Ruey and Wang, Yu-Shuen and Zhang, Eugene},
title = {{Hybrid Retrieval-Regression for Motion-Driven Loose-Fitting Garment Animation}},
author = {Lee, Myeongjin and Libao, Emmanuel Ian and Lee, Sung-Hee},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-295-0},
DOI = {10.2312/pg.20251259}
}