metadata
license: mit
library_name: pytorch
tags:
- computer-vision
- 3d-gaussian-splatting
- gaussian-splatting
- super-resolution
- eccv-2026
- pytorch
pipeline_tag: image-to-3d
AnchorSplat 20x Checkpoint
This repository hosts the released 20x checkpoint for AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting (ECCV 2026).
- Paper: https://arxiv.org/abs/2607.01290
- Code: https://github.com/zhude233/AnchorSplat
- Checkpoint:
anchorsplat_20x.pth - SHA256:
ad05f8b965c002c1f62cea53e4ce10ed4804bbc433375afa5f411f236d1b79a3
Usage
Download the checkpoint and place it at:
checkpoints/anchorsplat_20x.pth
or pass it explicitly:
WEIGHTS=/path/to/anchorsplat_20x.pth \
bash scripts/inference_external.sh examples/lgm_sample.ply outputs/lgm_sample_refined.ply lgm
Notes
AnchorSplat is designed for fast, generalizable, plug-and-play enhancement of low-quality 3D Gaussian Splatting assets. For external PLY inputs, please follow the input format and normalization instructions in the GitHub README.
Citation
@article{zhu2026anchorsplat,
title={AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting},
author={Zhu, Dexu and Shao, Jiangnan and Wang, Xiaofeng and Duan, Junxian and Cao, Jie and Zhu, Zheng and Huang, Huaibo},
journal={arXiv preprint arXiv:2607.01290},
year={2026},
eprint={2607.01290},
archivePrefix={arXiv},
primaryClass={cs.CV},
doi={10.48550/arXiv.2607.01290},
url={https://arxiv.org/abs/2607.01290}
}