| --- |
| license: apache-2.0 |
| pipeline_tag: image-to-3d |
| tags: |
| - gaussian-splatting |
| - 3d |
| - surface-reconstruction |
| --- |
| |
| # Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction |
|
|
| This repository provides the reconstructed meshes and resources for the paper [Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction](https://huggingface.co/papers/2605.12494). |
|
|
| **Authors**: Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xiaohan Yu, Lin Gu, Gim Hee Lee. |
|
|
| * [📚 Paper](https://huggingface.co/papers/2605.12494) |
| * [🌐 Project Page](https://fictionarry.github.io/AmbiSuR-Proj/) |
| * [💻 Code](https://github.com/Fictionarry/AmbiSuR) |
|
|
| ## Overview |
| AmbiSuR is a framework that explores an intrinsic solution upon Gaussian Splatting for photometric ambiguity-robust surface 3D reconstruction. By revisiting built-in primitive-wise ambiguities, the framework introduces a photometric disambiguation constraint and an ambiguity indication module to identify and guide the correction of underconstrained reconstructions, achieving high-performance surface formation in challenging scenarios. |
|
|
| ## Reconstruction on Tanks and Temples and DTU Datasets |
|
|
| Here we provide the reconstructed meshes of the paper's experiments from AmbiSuR. |
|
|
| You can browse all the released meshes at: |
|
|
| - `ambisur-<dataset>-meshes-eval/`: The meshes on DTU/TnT datasets, with strict filtering strategy for evaluation. |
| - `ambisur-<dataset>-meshes-vis/`: The meshes on DTU/TnT datasets, with loose filtering strategy for visualization. |
|
|
| Metrics shall be reproduced with the results with postfix of `-eval`. |
|
|
| ## Download |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| snapshot_download(repo_id="Fictionary/AmbiSuR", cache_dir='./AmbiSuR/results', local_dir ='./AmbiSuR/results') |
| ``` |
| or use Git to clone this repository with LFS. |
|
|
| ## Citation |
| ```bibtex |
| @inproceedings{li2026ambisur, |
| title={Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction}, |
| author={Li, Jiahe and Zhang, Jiawei and Bai, Xiao and Zheng, Jin and Yu, Xiaohan and Gu, Lin and Lee, Gim Hee}, |
| booktitle={International Conference on Machine Learning}, |
| year={2026}, |
| organization={PMLR} |
| } |
| ``` |
