metadata
license: apache-2.0
pipeline_tag: image-to-3d
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}
}