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Computer Science > Computer Vision and Pattern Recognition

Title: TELA: 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. Project page: this http URL
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2404.16748 [cs.CV]
  (or arXiv:2404.16748v1 [cs.CV] for this version)

Submission history

From: Junting Dong [view email]
[v1] Thu, 25 Apr 2024 17:05:38 GMT (10644kb,D)

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