| --- |
| license: apache-2.0 |
| task_categories: |
| - image-to-3d |
| - text-to-3d |
| language: |
| - en |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| <p align="center"> |
| <img src="assets/logo.png" alt="Alchemy3D" width="150" height="150" valign="middle" /> |
| <strong valign="middle" style="font-size: 2.4em;">Alchemy3D-1M</strong> |
| </p> |
| <p align="center"> |
| <b>A million-scale dataset 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://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://huggingface.co/libadi/Alchemy3D"><img src="https://img.shields.io/badge/🤗-Model-yellow.svg" alt="Hugging Face Model"></a> |
| <a href="https://www.modelscope.cn/datasets/libd55/Alchemy3D-1M"><img src="https://img.shields.io/badge/-Dataset-624AFF.svg?logo=modelscope&logoColor=white&labelColor=555" alt="ModelScope Dataset"></a> |
| <a href="https://huggingface.co/datasets/libadi/GEdit3D-Bench"><img src="https://img.shields.io/badge/🤗-GEdit3D--Bench-yellow.svg" alt="Benchmark"></a> |
| </p> |
|
|
| <p align="center"> |
| <img src="assets/teaser.png" alt="Alchemy3D-1M dataset teaser: a gallery of edited 3D assets." width="100%" /> |
| </p> |
|
|
| **Alchemy3D-1M** is the training corpus for [Alchemy3D](https://github.com/libd1/Alchemy3D): source–target 3D editing pairs on PBR-ready assets, with text instructions and image conditions. It contains **1.25M unique assets** and **1.38M editing pairs** across **7 edit types**. |
|
|
| Due to Hugging Face storage limits, this repository includes only training metadata, structured latents at resolution 512, and rendered conditions. For GLBs and latents at resolution 1024, please use the ModelScope counterpart [Alchemy3D-1M](https://www.modelscope.cn/datasets/libd55/Alchemy3D-1M). |
|
|
| ## Dataset Layout |
| The dataset contain encoded latents for sparse structure (`ss_latents`), geometry (`shape_latents/512`), PBR material (`pbr_latents/512`). `csv` files are metadata. |
|
|
| Latents are packed as `part_XXX.zip` shards. |
|
|
| ## Usage |
|
|
| Download the dataset: |
|
|
| ```bash |
| hf download libadi/Alchemy3D-1M --repo-type dataset --local-dir Alchemy3D-1M |
| ``` |
|
|
| Then unzip all zip files. |
|
|
| ## License |
|
|
| Apache License 2.0. Downstream 3D generators and renderers you apply to these assets may have their own terms. |
|
|
| ## 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}, |
| } |
| ``` |
