Access the GR3EN model weights
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GR3EN — License & Terms of Use
By requesting access to this repository you acknowledge and agree to the
following:
- License. The GR3EN fine-tuned weights are released under the
Apache License 2.0. The base model (Wan2.2-TI2V-5B) and SAM 2 are
redistributed under their respective licenses (Apache-2.0), which you
also agree to comply with. - Intended use. The model is intended for research and creative
applications: relighting of videos and 3D scenes. - Prohibited use. You will not use the model to produce content that
is unlawful, deceptive (including undisclosed synthetic or edited
media of real people or events), harassing, or that infringes the
privacy or intellectual-property rights of others. - Attribution. If you use the model in academic work, you agree to
cite the GR3EN paper (SIGGRAPH 2026). - No warranty. The model is provided "AS IS", without warranties or
conditions of any kind, as stated in the Apache License 2.0.
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GR3EN: Generative Relighting for 3D Environments
GR3EN (SIGGRAPH 2026) is a relighting model that finetunes Wan2.2-TI2V-5B for 3D-aware video generation with controllable lighting. Given input images and light control masks, GR3EN generates relit video sequences.
- Project page: https://gr3en-relight.github.io
- Code: https://github.com/xyxingx/gr3en
- Interactive demo: https://huggingface.co/spaces/xyxingx/GR3EN
Repository contents
| Path | Description |
|---|---|
gr3en_weights.pt |
GR3EN fine-tuned DiT + ControlNet weights |
wan2.2-ti2v-5b/ |
Wan2.2-TI2V-5B base model, VAE and prompt embeddings |
sam2/sam2.1_hiera_large.pt |
SAM 2 checkpoint (interactive demos only) |
Usage
Download all files and arrange them under gr3en/inference/checkpoints/ as
described in the GitHub README, then run
the Studio demo or batch inference.
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Base model
Wan-AI/Wan2.2-TI2V-5B