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--- |
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language: |
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- en |
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license: mit |
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size_categories: |
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- n<1K |
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pretty_name: Edit3D-Bench |
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tags: |
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- 3D |
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- Editing |
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task_categories: |
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- image-to-3d |
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--- |
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This repository contains Edit3D-Bench, a 3D editing benchmark proposed in the paper [Feedforward 3D Editing via Text-Steerable Image-to-3D](https://huggingface.co/papers/2512.13678). |
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Project page: https://glab-caltech.github.io/steer3d/ |
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Code: https://github.com/ziqi-ma/Steer3D |
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The `metadata/` directory stores metadata information (the source and target object guid, and editing text) for texture, removal, and addition - each in a separate `.csv` file. |
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The `data/` directory contains source images (of unedited object), glbs of both source and target objects, and [TRELLIS](trellis3d.github.io) latents of both source and target objects, each indexed with the object guid. |
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### Sample Usage |
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This dataset is designed to benchmark 3D editing capabilities. To use it for evaluation with the associated [Steer3D codebase](https://github.com/ziqi-ma/Steer3D), follow these steps: |
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1. **Clone the dataset:** |
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```bash |
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git lfs install |
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git clone https://huggingface.co/datasets/ziqima/Edit3D-Bench |
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``` |
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2. **Set up the Steer3D environment:** |
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The Steer3D model requires a specific environment. Refer to the [Steer3D GitHub repository](https://github.com/ziqi-ma/Steer3D) for the latest setup instructions. A typical setup involves: |
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```bash |
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conda env create -f environment.yml |
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conda activate steer3d |
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``` |
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Note that libraries `kaolin`, `nvdiffrast`, `diffoctreerast`, `mip-splatting`, and `vox2seq` might need manual installation. Please refer to [this setup script from TRELLIS](https://github.com/microsoft/TRELLIS/blob/main/setup.sh) for installation of these dependencies. |
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3. **Evaluate on the Benchmark (Texture Example):** |
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Once the dataset is cloned and the Steer3D environment is active, you can run evaluation scripts. First, ensure `PYTHONPATH` is set to the path of your Steer3D clone. Then, update the `val_dataset` path in `configs/stage3_controlnet.json` within the Steer3D repository to `[path-to-Edit3D-Bench-clone]/metadata/texture.csv`. |
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```bash |
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python inference/inference_texture.py \ |
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--stage1_checkpoint [path-to-checkpoints]/stage1/base.pt \ |
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--stage1_config configs/stage1_controlnet.json \ |
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--stage2_controlnet_checkpoint [path-to-checkpoints]/stage2/controlnet.pt \ |
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--stage2_base_checkpoint [path-to-checkpoints]/stage2/base.pt \ |
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--stage2_config configs/stage2_controlnet.json \ |
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--output_dir visualizations/output \ |
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--num_examples 150 \ |
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--num_seeds 3 \ |
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--split val |
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``` |
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### Citation |
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If you find our work helpful, please cite using the following BibTeX entry: |
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```bibtex |
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@misc{ma2025feedforward3deditingtextsteerable, |
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title={Feedforward 3D Editing via Text-Steerable Image-to-3D}, |
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author={Ziqi Ma and Hongqiao Chen and Yisong Yue and Georgia Gkioxari}, |
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year={2025}, |
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eprint={2512.13678}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2512.13678}, |
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} |
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``` |
