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README.md

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+---
+license: mit
+library_name: pytorch
+tags:
+  - 3d-generation
+  - voxel-generation
+  - 3d-editing
+  - diffusion
+  - image-to-3d
+  - text-to-3d
+  - trellis
+pipeline_tag: image-to-3d
+---
+
+# DVD: Discrete Voxel Diffusion for 3D Generation and Editing
+
+This repository hosts the pretrained DVD checkpoints for **Discrete Voxel Diffusion for 3D Generation and Editing**.
+
+DVD is a discrete diffusion pipeline that generates or edits a pure `64^3` voxel grid. The voxel output can be used directly, exported as a cubified voxel mesh, or passed as the sparse-structure anchor for [TRELLIS](https://github.com/microsoft/TRELLIS) stage 2 to produce final mesh and 3D Gaussian assets.
+
+- Paper: [arXiv:2605.07971](https://arxiv.org/abs/2605.07971)
+- Spaces: [DVD Image](https://huggingface.co/spaces/Zhengrui/dvd-image), [DVD Text](https://huggingface.co/spaces/Zhengrui/dvd-text)
+
+## Checkpoints
+
+| Variant | Files | Use case |
+| --- | --- | --- |
+| Image generation | `dvd_img.json`, `dvd_img.safetensors` | image-conditioned voxel generation |
+| Image editing | `dvd_img_BSP_ft.json`, `dvd_img_BSP_ft.safetensors` | image-conditioned voxel editing |
+| Text generation | `dvd_text.json`, `dvd_text.safetensors` | text-conditioned voxel generation |
+| Text editing | `dvd_text_BSP_ft.json`, `dvd_text_BSP_ft.safetensors` | text-conditioned voxel editing |
+
+## Minimal Usage
+
+```python
+from dvd import DVDImageToVoxelPipeline, DVDTextToVoxelPipeline
+
+repo_id = "Zhengrui/dvd"
+
+image_dvd = DVDImageToVoxelPipeline.from_pretrained(repo_id, variant="base", device="cuda")
+image_edit_dvd = DVDImageToVoxelPipeline.from_pretrained(repo_id, variant="bsp", device="cuda")
+
+text_dvd = DVDTextToVoxelPipeline.from_pretrained(repo_id, variant="base", device="cuda")
+text_edit_dvd = DVDTextToVoxelPipeline.from_pretrained(repo_id, variant="bsp", device="cuda")
+```
+
+Example image-conditioned generation:
+
+```python
+from PIL import Image
+from dvd import DVDImageToVoxelPipeline, export_cubified_voxels
+
+image = Image.open("assets/example_image/T.png")
+dvd = DVDImageToVoxelPipeline.from_pretrained("Zhengrui/dvd", variant="base", device="cuda")
+voxels = dvd.sample_voxels(image, seed=42, steps=256)
+export_cubified_voxels(voxels, "dvd_voxels.glb")
+```
+
+## Voxel Convention
+
+DVD stores voxel outputs as:
+
+```text
+samples: [B, D, H, W]
+coords:  [N, 4] as [batch, x, y, z]
+```
+
+Saved `.npy` coordinate files usually omit the batch dimension and can be loaded back with `as_voxel_output(coords, resolution=64)`.
+
+## Notes
+
+These files are the DVD voxel-stage checkpoints. TRELLIS stage-2 checkpoints are loaded separately from the official TRELLIS model repositories, such as `microsoft/TRELLIS-image-large` and `microsoft/TRELLIS-text-large`.
+
+## Citation
+
+```bibtex
+@misc{xiang2026dvddiscretevoxeldiffusion,
+      title={DVD: Discrete Voxel Diffusion for 3D Generation and Editing},
+      author={Zhengrui Xiang and Jiaqi Wu and Fupeng Sun and Heliang Zheng and Yingzhen Li},
+      year={2026},
+      eprint={2605.07971},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2605.07971},
+}
+```