Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects
<|reference_start|>Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects: The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and fast generation capabilities, one of which is texture generation for 3D objects. Although recent texture generation methods achieve impressive results by using text-to-image networks, the combination of global consistency, quality, and speed, which is crucial for advancing texture generation to real-world applications, remains elusive. To that end, we introduce Meta 3D TextureGen: a new feedforward method comprised of two sequential networks aimed at generating high-quality and globally consistent textures for arbitrary geometries of any complexity degree in less than 20 seconds. Our method achieves state-of-the-art results in quality and speed by conditioning a text-to-image model on 3D semantics in 2D space and fusing them into a complete and high-resolution UV texture map, as demonstrated by extensive qualitative and quantitative evaluations. In addition, we introduce a texture enhancement network that is capable of up-scaling any texture by an arbitrary ratio, producing 4k pixel resolution textures.<|reference_end|>
@article{bensadoun2024meta,
    title={Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D
  Objects},
    author={Raphael Bensadoun, Yanir Kleiman, Idan Azuri, Omri Harosh, Andrea
  Vedaldi, Natalia Neverova, Oran Gafni},
    journal={arXiv preprint arXiv:2407.02430},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.02430},
    primaryClass={cs.CV cs.AI cs.GR cs.LG}
}