Request access to the World Tracing object model

These checkpoints are released for non-commercial research use under the CC BY-NC-ND 4.0 license (Attribution-NonCommercial-NoDerivatives). Please share a few details below so we can keep a light audit trail of how the weights are used in the wild. Requests are reviewed manually, typically within 1-3 business days.

World Tracing — Object Model (6-layer, r75b)

🆕 Update (2026-09-23): model.pt has been updated to a new, stronger checkpoint. Please git pull the inference code together with the new weights. The previous weights remain available in this repo's commit history.

Access

The checkpoints in this repo are released under the CC BY-NC-ND 4.0 license, but downloads are gated so we can keep a light audit trail of how the model is used. To download:

Scroll up and fill in the "Submit access request" form (basic contact info + a short note on intended use).
We review every request manually, usually within 1-3 business days. You will receive an email from Hugging Face once your request is approved.
After approval, log in with huggingface-cli login (or set HF_TOKEN) and run any of the inference examples from the GitHub repo — the wt package picks the token up automatically and --ckpt r75b / r69e / r76 triggers a normal hf_hub_download.

Note: this is a manual review flow, not an auto-approve click-through. We read every request individually, so please give a one-line description of what you plan to use the weights for.

EMA-only release weights for the r75b object model from World Tracing: Generative Pixel-Aligned Geometry Beyond the Visible.

Repo: https://github.com/haoz19/world-tracing
Project page: https://haoz19.github.io/world-tracing-page/
Config name: r75b
Architecture: MultilayerXYZModel (DINOv2-vit-L encoder + 6-layer diffusion head), 1.7 B params
Input: 504 × 504 RGBA, alpha-matted single object
Output: per-layer XYZ in camera space, 6 stacked depth maps (visible surface + 5 occluded layers behind it)
Training data: Objaverse renders + curated public 3D-asset corpora

Files

File	Size	Format
`model.pt`	6.21 GB	bare `state_dict`, float32

This release contains the EMA weights only (no optimizer / config / gradients) so the download is ~26 % of the original training checkpoint.

Usage

git clone https://github.com/haoz19/world-tracing
cd world-tracing
pip install -e ".[viz,bg]"

python examples/infer_rgba.py \
    --image  examples/test_images/object/obj014_leather_briefcase.png \
    --ckpt   r75b \
    --config r75b \
    --out    /tmp/wt_obj.rrd

Bare --ckpt r75b triggers huggingface_hub.hf_hub_download against this repo and caches the weights under ~/.cache/huggingface/hub/. First run downloads 6.21 GB; subsequent runs are instant.

Citation

@misc{zhang2026worldtracinggenerativepixelaligned,
  title         = {World Tracing: Generative Pixel-Aligned Geometry Beyond the Visible},
  author        = {Hao Zhang and Mohamed El Banani and Jen-Hao Cheng and Paul Zhang
                   and Yi Hua and Ben Mildenhall and Christoph Lassner
                   and Narendra Ahuja and Gengshan Yang},
  year          = {2026},
  eprint        = {2606.13652},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  url           = {https://arxiv.org/abs/2606.13652}
}

License

CC BY-NC-ND 4.0 (Attribution-NonCommercial-NoDerivatives) — see the GitHub repo. Non-commercial research use only.

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Paper for haoz19/object-model-6layer

World Tracing: Generative Pixel-Aligned Geometry Beyond the Visible

Paper • 2606.13652 • Published Jun 11 • 16