Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
110 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

TELA: Text to Layer-wise 3D Clothed Human Generation (2404.16748v1)

Published 25 Apr 2024 in cs.CV

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: http://jtdong.com/tela_layer/

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (7)
  1. Junting Dong (19 papers)
  2. Qi Fang (10 papers)
  3. Zehuan Huang (9 papers)
  4. Xudong Xu (20 papers)
  5. Jingbo Wang (138 papers)
  6. Sida Peng (70 papers)
  7. Bo Dai (245 papers)
Citations (3)

Summary

We haven't generated a summary for this paper yet.