😇FatesGS: Fast and Accurate Sparse-View Surface Reconstruction Using Gaussian Splatting with Depth-Feature Consistency

AAAI 2025

Han Huang*  Yulun Wu*  Chao Deng  Ge Gao†  Ming Gu  Yu-Shen Liu
Tsinghua University
*Equal contribution. †Corresponding author.

TODO

• Code release

Overview

We propose FatesGS for sparse-view surface reconstruction, taking full advantage of the Gaussian Splatting pipeline. Compared with previous methods, our approach neither requires long-term per-scene optimization nor costly pre-training.

Citation

If you find our work useful in your research, please consider citing:

@inproceedings{huang2025fatesgs,
    title={FatesGS: Fast and Accurate Sparse-View Surface Reconstruction Using Gaussian Splatting with Depth-Feature Consistency},
    author={Han Huang and Yulun Wu and Chao Deng and Ge Gao and Ming Gu and Yu-Shen Liu},
    booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
    year={2025}
}