InTeX: Interactive Text-to-texture Synthesis via Unified Depth-aware Inpainting

Jiaxiang Tang, Ruijie Lu, Xiaokang Chen, Xiang Wen, Gang Zeng +1 more
3/18/2024
cs.CV

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Abstract

Text-to-texture synthesis has become a new frontier in 3D content creation thanks to the recent advances in text-to-image models. Existing methods primarily adopt a combination of pretrained depth-aware diffusion and inpainting models, yet they exhibit shortcomings such as 3D inconsistency and limited controllability. To address these challenges, we introduce InteX, a novel framework for interactive text-to-texture synthesis. 1) InteX includes a user-friendly interface that facilitates interaction and control throughout the synthesis process, enabling region-specific repainting and precise texture editing. 2) Additionally, we develop a unified depth-aware inpainting model that integrates depth information with inpainting cues, effectively mitigating 3D inconsistencies and improving generation speed. Through extensive experiments, our framework has proven to be both practical and effective in text-to-texture synthesis, paving the way for high-quality 3D content creation.

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Cite this paper

@article{tang2024intex,
  title  = {InTeX: Interactive Text-to-texture Synthesis via Unified Depth-aware Inpainting},
  author = {Jiaxiang Tang and Ruijie Lu and Xiaokang Chen and Xiang Wen and Gang Zeng and Ziwei Liu},
  year   = {2024},
  eprint = {2403.11878},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.11878v1}
}

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