Sparis: Neural Implicit Surface Reconstruction of Indoor Scenes from Sparse Views

AAAI 2025 Oral

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

TODO

• Code release

Overview

In this paper, we propose a new method, named Sparis, for indoor surface reconstruction from sparse views. Specifically, we investigate the impact of monocular priors on sparse scene reconstruction, introducing a novel prior based on inter-image matching information. Our prior offers more accurate depth information while ensuring cross-view matching consistency.

Citation

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

@inproceedings{wu2025sparis,
    title={Sparis: Neural Implicit Surface Reconstruction of Indoor Scenes from Sparse Views},
    author={Yulun Wu and Han Huang and Wenyuan Zhang and Chao Deng and Ge Gao and Ming Gu and Yu-Shen Liu},
    booktitle={AAAI Conference on Artificial Intelligence},
    year={2025}
}