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Dvd

This repository hosts the pretrained DVD checkpoints for Discrete Voxel Diffusion for 3D Generation and Editing.

Sourcehuggingface.co/Zhengrui/dvd/tree/bfc4d6873d1283e342c1a68b61a4b3bb31de1d6b
KindOtherVersionImg BSP ftBgrade

Model source

Kind
Other
File size
1.50–1.55 GB
Version
vImg BSP ft
Updated
Oct 10, 2026
Source
Hugging Face

Source description

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 stage 2 to produce final mesh and 3D Gaussian assets.

Checkpoints

VariantFilesUse case
Image generationdvd_img.json, dvd_img.safetensorsimage-conditioned voxel generation
Image editingdvd_img_BSP_ft.json, dvd_img_BSP_ft.safetensorsimage-conditioned voxel editing
Text generationdvd_text.json, dvd_text.safetensorstext-conditioned voxel generation
Text editingdvd_text_BSP_ft.json, dvd_text_BSP_ft.safetensorstext-conditioned voxel editing

Minimal Usage

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:

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:

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

@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},
}

Sources

1 source
Hugging FacePrimaryVersion bfc4d6873d1283e342c1a68b61a4b3bb31de1d6b
huggingface.co/Zhengrui/dvd/tree/bfc4d6873d1283e342c1a68b61a4b3bb31de1d6b

Verified Oct 10

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Model artifacts

4 artifacts

dvd_img_BSP_ft.safetensors

safetensors · 1.55 GB · SHA-256 6e053b0fdab3…a307 · Hugging Face

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dvd_img.safetensors

safetensors · 1.55 GB · SHA-256 b73ba077d29a…7b69 · Hugging Face

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dvd_text_BSP_ft.safetensors

safetensors · 1.50 GB · SHA-256 32bf1fb84c39…74a4 · Hugging Face

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dvd_text.safetensors

safetensors · 1.50 GB · SHA-256 1b928adb953b…46db · Hugging Face

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Source excerpts

2 excerpts
ReadmeAug 1huggingface.co/Zhengrui/dvd

--- 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 batc...

NoteAug 1huggingface.co/Zhengrui/dvd

Source context: 0 downloads · 1 likes · Pipeline image-to-3d · Library pytorch · Repo Zhengrui/dvd