3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image

Project Page | Paper | GitHub

3D-Fixer introduces a novel In-Place Completion paradigm to create high-fidelity 3D scenes from a single image. It extends 3D object generative priors to generate complete 3D assets conditioned on partially visible point clouds, using fragmented geometry as a spatial anchor to preserve layout fidelity without the need for time-consuming pose optimization.

Sample Usage

The model can be loaded using the following code snippet from the official repository:

# Load the pretrained model
ThreeDFixerPipeline.from_pretrained("HorizonRobotics/3D-Fixer")

Dataset

The model was trained on ARSG-110K, a large-scale scene-level dataset comprising over 110K diverse scenes and 3M annotated images with high-fidelity 3D ground truth.

Citation

@inproceedings{yin2026tdfixer,
  title={3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image},
  author={Yin, Ze-Xin and Liu, Liu and Wang, Xinjie and Sui, Wei and Su, Zhizhong and Yang, Jian and Xie, jin},
  booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
  year={2026}
}