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Fictionary/
GeoSVR

image-to-3d

2509.18090

apache-2.0

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GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction

This repository provides the reconstructed meshes and resources for the paper GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction, which presents an explicit voxel-based framework for accurate, detailed, and complete surface reconstruction.

Reconstruction on Tanks and Temples and DTU Datasets

Here we provide the reconstructed meshes of the paper's experiments from GeoSVR.

You can browse all the released meshes at:

meshes_complete/: The complete meshes of the two datasets.
DTU_meshes_eval/: The meshes on DTU datasets, with strict filtering strategy for evaluation.
TnT_meshes_eval/: The meshes on TnT datasets, with strict filtering strategy for evaluation.

Metrics shall be reproduced with the results with postfix of _eval.

Download

python

from huggingface_hub import snapshot_download
snapshot_download(repo_id="Fictionary/GeoSVR", cache_dir='./GeoSVR/results', local_dir ='./GeoSVR/results')

or use Git to clone this repository with LFS.

Citation

bibtex

@article{li2025geosvr,
  title={GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction},
  author={Li, Jiahe and Zhang, Jiawei and Zhang, Youmin and Bai, Xiao and Zheng, Jin and Yu, Xiaohan and Gu, Lin},
  journal={Advances in Neural Information Processing Systems},
  year={2025}
}