Update Edit3D-Bench dataset card with correct license, paper, project page, and code links
Browse filesThis PR improves the Edit3D-Bench dataset card by:
- Correcting the license in the metadata from Apache-2.0 to MIT, aligning with the license specified in the associated GitHub repository.
- Adding direct links to the Hugging Face paper (`https://huggingface.co/papers/2508.19247`), the main project page (`https://huanngzh.github.io/VoxHammer-Page/`), and the GitHub repository (`https://github.com/Nelipot-Lee/VoxHammer`) for improved discoverability.
- Incorporating the paper title and link into the introductory description.
- Enhancing the BibTeX citation with a `url` field pointing to the Hugging Face paper page.
README.md
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---
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license: apache-2.0
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language:
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- en
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- 3D-Generation
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- 3D-Edit
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task_categories:
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- image-to-3d
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- text-to-3d
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---
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# Edit3D-Bench
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-
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This dataset comprises 100 high-quality 3D models, with 50 selected from Google Scanned Objects (GSO) and 50 from PartObjaverse-Tiny.
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For each model, we provide 3 distinct editing prompts. Each prompt is accompanied by a complete set of annotated 3D assets, including
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* original 3D asset with rendered images
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## 🧷 Citation
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```
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@article{li2025voxhammer,
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title = {VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space},
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author = {Li, Lin and Huang, Zehuan and Feng, Haoran and Zhuang, Gengxiong and Chen, Rui and Guo, Chunchao and Sheng, Lu},
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journal = {arXiv preprint arXiv:2508.19247},
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year = {2025}
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}
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```
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---
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language:
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- en
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license: mit
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task_categories:
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- image-to-3d
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- text-to-3d
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tags:
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- 3D-Generation
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- 3D-Edit
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---
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# Edit3D-Bench
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[Paper](https://huggingface.co/papers/2508.19247) | [Project Page](https://huanngzh.github.io/VoxHammer-Page/) | [Code](https://github.com/Nelipot-Lee/VoxHammer)
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**Edit3D-Bench** is a benchmark for 3D editing evaluation, introduced in the paper [VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space](https://huggingface.co/papers/2508.19247).
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This dataset comprises 100 high-quality 3D models, with 50 selected from Google Scanned Objects (GSO) and 50 from PartObjaverse-Tiny.
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For each model, we provide 3 distinct editing prompts. Each prompt is accompanied by a complete set of annotated 3D assets, including
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* original 3D asset with rendered images
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## 🧷 Citation
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```bibtex
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@article{li2025voxhammer,
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title = {VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space},
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author = {Li, Lin and Huang, Zehuan and Feng, Haoran and Zhuang, Gengxiong and Chen, Rui and Guo, Chunchao and Sheng, Lu},
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journal = {arXiv preprint arXiv:2508.19247},
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year = {2025},
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url = {https://huggingface.co/papers/2508.19247}
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}
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```
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