Text to Layer-Wise 3D Clothed Human Generation
Abstract
This paper addresses the task of 3D clothed human generation from textural descriptions. Previous works usually encode the human body and clothes as a holistic model and generate the whole model in a single-stage optimization, which makes them struggle for clothing editing and meanwhile lose fine-grained control over the whole generation process. To solve this, we propose a layer-wise clothed human representation combined with a progressive optimization strategy, which produces clothing-disentangled 3D human models while providing control capacity for the generation process. The basic idea is progressively generating a minimal-clothed human body and layer-wise clothes. During clothing generation, a novel stratified compositional rendering method is proposed to fuse multi-layer human models, and a new loss function is utilized to help decouple the clothing model from the human body. The proposed method achieves high-quality disentanglement, which thereby provides an effective way for 3D garment generation. Extensive experiments demonstrate that our approach achieves state-of-the-art 3D clothed human generation while also supporting cloth editing applications such as virtual try-on.
Cite
Text
Dong et al. "Text to Layer-Wise 3D Clothed Human Generation." Proceedings of the European Conference on Computer Vision (ECCV), 2024. doi:10.1007/978-3-031-72698-9_2Markdown
[Dong et al. "Text to Layer-Wise 3D Clothed Human Generation." Proceedings of the European Conference on Computer Vision (ECCV), 2024.](https://mlanthology.org/eccv/2024/dong2024eccv-text/) doi:10.1007/978-3-031-72698-9_2BibTeX
@inproceedings{dong2024eccv-text,
title = {{Text to Layer-Wise 3D Clothed Human Generation}},
author = {Dong, Junting and Fang, Qi and Huang, Zehuan and Xu, Xudong and Wang, Jingbo and Peng, Sida and Dai, Bo},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2024},
doi = {10.1007/978-3-031-72698-9_2},
url = {https://mlanthology.org/eccv/2024/dong2024eccv-text/}
}