ARSG-110K

Project Page | Paper | GitHub

ARSG-110K is a large-scale scene-level dataset comprising over 110K diverse scenes and 3M annotated images with high-fidelity 3D ground truth. It is designed to support the training and evaluation of compositional 3D scene generation and in-place completion models. The dataset provides accurate 3D object-level ground-truth, layout, and annotations.

This dataset was introduced as part of the paper: 3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image.

Dataset Details

• Source Data: The Objaverse_github.csv and ObjaverseXL_sketchfab.csv are subsets of those from TRELLIS-500K.
• Assets: The hdrs.zip, materials_floor.zip, and materials_wall.zip contain assets from BlenderKit.
• Examples: This repository provides renderings of 1000 example scenes.

Accessing the Data

Please follow the detailed instructions on the official GitHub repository to access the full dataset beyond the example renderings.

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}
}