🎨 ReStyle3D: Scene-Level Appearance Transfer with Semantic Correspondences

ACM SIGGRAPH 2025

Official implementation of the paper titled "Scene-level Appearance Transfer with Semantic Correspondences".

Liyuan Zhu¹, Shengqu Cai^1,*, Shengyu Huang^2,*, Gordon Wetzstein¹, Naji Khosravan³, Iro Armeni¹

¹Stanford University, ²NVIDIA Research, ³Zillow Group | ^* denotes equal contribution

@inproceedings{zhu2025_restyle3d,
    author = {Liyuan Zhu and Shengqu Cai and Shengyu Huang and Gordon Wetzstein and Naji Khosravan and Iro Armeni},
    title = {Scene-level Appearance Transfer with Semantic Correspondences},
    booktitle = {ACM SIGGRAPH 2025 Conference Papers},
    year = {2025},
  }

We introduce ReStyle3D, a novel framework for scene-level appearance transfer from a single style image to a real-world scene represented by multiple views. This method combines explicit semantic correspondences with multi-view consistency to achieve precise and coherent stylization.

(Under construction)