metadata
license: mit
pipeline_tag: image-to-3d
StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views
This repository contains the pretrained weights for StructSplat, a feed-forward and generalizable 3D Gaussian reconstruction framework that operates directly on uncalibrated images without requiring camera parameters.
- Paper: StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views
- Project Page: https://structsplat.github.io
- Code: https://github.com/J-C-Zhao/StructSplat
Installation & Evaluation
To set up the environment and run training or evaluation, please refer to the instructions in the GitHub Repository.
Setup Environment
conda create -n structsplat python=3.10.19
conda activate structsplat
pip install torch==2.4.0 torchvision==0.19.0 -i https://download.pytorch.org/whl/cu118
pip install -r requirements.txt
Evaluation
Run the following command to evaluate the model:
python evaluation.py -c config/dl3dv.yaml
Citation
If you find this work useful, please cite the paper:
@inproceedings{zhao2026structsplat,
title={StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views},
author={Zhao, Jia-Chen and Chen, Beiqi and Chen, Xinyang and Wang, Guangcong and Nie, Liqing},
booktitle={European Conference on Computer Vision},
year={2026}
}