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lalala125/GSROR
GSROR is a image-to-3d model from lalala125. Use it for the image-to-3d task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-nc-4.0.
This repository contains the official checkpoints and results for GS-ROR<sup2</sup, a novel method presented in the paper GS-ROR<sup2</sup: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Recons…
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Updated Aug 15, 2025
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From the Hugging Face model README
This repository contains the official checkpoints and results for GS-ROR<sup>2</sup>, a novel method presented in the paper GS-ROR<sup>2</sup>: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction. This work will be presented at ACM TOG 2025.
GS-ROR<sup>2</sup> significantly advances 3D Gaussian splatting (3DGS) for inverse rendering, enabling the creation of high-quality relightable 3D assets.
<p align="middle"> <img src="https://nk-cs-zzl.github.io/projects/gsror/assets/images/angel_relit.gif" width="30%"/><img src="https://nk-cs-zzl.github.io/projects/gsror/assets/images/tbell_relit.gif" width="30%"/><img src="https://nk-cs-zzl.github.io/projects/gsror/assets/images/toaster_relit.gif" width="30%"/> </p> <p align="middle"> <img src="https://nk-cs-zzl.github.io/projects/gsror/assets/images/angel_mesh.gif" width="30%"/><img src="https://nk-cs-zzl.github.io/projects/gsror/assets/images/tbell_mesh.gif" width="30%"/><img src="https://nk-cs-zzl.github.io/projects/gsror/assets/images/toaster_mesh.gif" width="30%"/> </p>For detailed installation instructions, environment setup, and information on training and evaluation, please refer to the official GitHub repository.
To run a quick relighting video demo with the provided checkpoints:
git clone https://github.com/NK-CS-ZZL/GS-ROR.git
cd GS-ROR
pretrained folder.sh demo.sh
If you find our work useful for your research, please consider citing our paper:
@inproceedings{zhu_2025_gsror,
title={GS-ROR^2: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction},
author={Zhu, Zuo-Liang and Yang, Jian and Wang, Beibei},
journal = {ACM Transactions on Graphics (TOG)},
year={2025},
publisher = {ACM},
doi={10.1145/3759248},
}