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license: apache-2.0
task_categories:
- image-to-3d
- text-to-3d
language:
- en
size_categories:
- 1K<n<10K
tags:
- 3d
- 3d-editing
- benchmark
- evaluation
---
<p align="center">
<img src="assets/logo.png" alt="Alchemy3D" width="88" height="88" style="display:inline-block; vertical-align:middle; margin:0 12px 0 0;" />
<span style="display:inline-block; vertical-align:middle; font-size:2.4em; font-weight:700; line-height:1;">GEdit3D-Bench</span>
</p>
<p align="center">
<b>A large-scale, open-world benchmark for versatile 3D asset editing.</b>
</p>
<p align="center">
<a href="https://libd1.github.io/Alchemy3D-Project/"><img src="https://img.shields.io/badge/Project-Page-0A7F5F.svg" alt="Project Page"></a>
<a href="https://arxiv.org/abs/2609.34271"><img src="https://img.shields.io/badge/arXiv-Paper-b31b1b.svg" alt="arXiv"></a>
<a href="https://arxiv.org/pdf/2609.34271"><img src="https://img.shields.io/badge/Paper-PDF-red.svg" alt="PDF"></a>
<a href="https://github.com/libd1/Alchemy3D"><img src="https://img.shields.io/badge/-code-black.svg?logo=github&logoColor=white&labelColor=555" alt="Code"></a>
<a href="https://github.com/libd1/edit3dstudio"><img src="https://img.shields.io/badge/-evaluation-black.svg?logo=github&logoColor=white&labelColor=555" alt="Evaluation"></a>
<a href="https://huggingface.co/libadi/Alchemy3D"><img src="https://img.shields.io/badge/🤗-Model-yellow.svg" alt="Hugging Face Model"></a>
<a href="https://huggingface.co/datasets/libadi/Alchemy3D-1M"><img src="https://img.shields.io/badge/🤗-Alchemy3D--1M-yellow.svg" alt="Dataset"></a>
<a href="https://modelscope.cn/datasets/libd55/GEdit3D-Bench"><img src="https://img.shields.io/badge/-Dataset-624AFF.svg?logo=modelscope&logoColor=white&labelColor=555" alt="ModelScope Dataset"></a>
</p>
<p align="center">
<img src="assets/teaser.png" alt="GEdit3D-Bench construction and multi-dimensional evaluation overview." width="100%" />
</p>
**GEdit3D-Bench** is the evaluation benchmark for [Alchemy3D](https://github.com/libd1/Alchemy3D): an open-world 3D editing suite built from assets independent of the training data (newly synthesized content and curated Sketchfab assets). It contains **2,100** editing pairs over **6** edit types. Each item provides a **source asset**, **source / target captions**, **source / target images**, and an **editing instruction**. Evaluation jointly measures view quality, reference alignment, and MLLM-based scores.
A ModelScope mirror is also available at [libd55/GEdit3D-Bench](https://modelscope.cn/datasets/libd55/GEdit3D-Bench).
## Dataset Layout
The benchmark contains source assets (`glbs/`), condition images (`images/`), and metadata CSVs. `metadata.csv` indexes the **full** set (**2,100** pairs across `add`, `remove`, `replace`, `local_appearance`, `global_appearance`, `animation`). `metadata_small.csv` is the subset used for **MLLM / human scoring** (**420** pairs), kept smaller because these evaluations are expensive.
Each row provides a source asset, source/target captions, source/target images, an editing instruction, and an edit type.
## Usage
Download the benchmark:
```bash
hf download libadi/GEdit3D-Bench --repo-type dataset --local-dir GEdit3D-Bench
```
Evaluation code and baselines would be released at **[edit3dstudio](https://github.com/libd1/edit3dstudio)**.
## License
Apache License 2.0. Downstream 3D generators and renderers you apply to these assets may have their own terms. Sketchfab-sourced assets may carry additional terms from their original licenses.
## Citation
```bibtex
@misc{li2026scalingversatile3dassets,
title={Scaling Versatile 3D Assets Editing with a Million-Scale Dataset},
author={Badi Li and Tianxin Huang and Yu Zhou and Wei-Shi Zheng and Yi Ma and Shenghua Gao},
year={2026},
eprint={2609.34271},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2609.34271},
}
```
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