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| Página principal > Libros y colecciones > Capítulos de libros > A Generative multi-resolution pyramid and normal-conditioning 3D cloth draping |
| Publicación: | IEEE, 2024 |
| Descripción: | 10 pàg. |
| Resumen: | RGB cloth generation has been deeply studied in the related literature, however, 3D garment generation remains an open problem. In this paper, we build a conditional variational autoencoder for 3D garment generation and draping. We propose a pyramid network to add garment details progressively in a canonical space, i. e. unposing and unshaping the garments w. r. t. the body. We study conditioning the network on surface normal UV maps, as an intermediate representation, which is an easier problem to optimize than 3D coordinates. Our results on two public datasets, CLOTH3D and CAPE, show that our model is robust, controllable in terms of detail generation by the use of multi-resolution pyramids, and achieves state-of-the-art results that can highly generalize to unseen garments, poses, and shapes even when training with small amounts of data. The code can be found at: https://github. com/HunorLaczko/pyramid-drape. |
| Ayudas: | Agencia Estatal de Investigación PID2022-136436NB-I00 Agencia Estatal de Investigación PDC2022-133305-I00 Agencia Estatal de Investigación TED2021-131317B-I00 Agencia Estatal de Investigación PID2020-120611RB-I00 |
| Derechos: | Aquest material està protegit per drets d'autor i/o drets afins. Podeu utilitzar aquest material en funció del que permet la legislació de drets d'autor i drets afins d'aplicació al vostre cas. Per a d'altres usos heu d'obtenir permís del(s) titular(s) de drets. |
| Lengua: | Anglès |
| Documento: | Capítol de llibre ; recerca ; Versió acceptada per publicar |
| Materia: | 3D ; 3D computer vision ; Algorithms ; Applications ; Etc ; Generative models for image ; Video ; Virtual/augmented reality |
| Publicado en: | 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, p. 8694-8703, ISBN 979-8-3503-1892-0 |
Postprint |