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TomLjm/MUGen-VR-AnyFlow-Conditioner
MUGen-VR-AnyFlow-Conditioner is a image-to-video model from TomLjm. Use it for the image-to-video task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as other.
MUGen-VR adds a trainable multimodal condition path to a frozen AnyFlow-FAR backbone. ImageBind encodes text, image, and audio inputs; InternVideo2 encodes videos and retrieved references. Three fusion tokens, four re…
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From the Hugging Face model README
MUGen-VR adds a trainable multimodal condition path to a frozen AnyFlow-FAR backbone.
ImageBind encodes text, image, and audio inputs; InternVideo2 encodes videos and retrieved
references. Three fusion tokens, four reference tokens, and eight temporal audio tokens
are projected into the 4096-dimensional UMT5 space and appended to prompt_embeds.
The release contains only project-owned lightweight artifacts:
It excludes AnyFlow, ImageBind, and InternVideo2 weights, MSR-VTT media, cached features, and optimizer state. These dependencies must be obtained under their upstream terms.
The fixed evaluation uses 40 held-out samples with generation seed 42. Condition scale
0.05 was selected on a separate validation split.
| Metric | Frozen AnyFlow | MUGen-VR | Change |
|---|---|---|---|
| Subject consistency | 0.88328 | 0.88596 | +0.00268 |
| Motion smoothness | 0.98201 | 0.98248 | +0.00046 |
| Temporal flickering | 0.96963 | 0.96978 | +0.00014 |
MUGen-VR reduces subject-consistency error by 2.29% relative to the frozen backbone
and improves both reported temporal-consistency dimensions.
Please cite AnyFlow, ImageBind, InternVideo2, MSR-VTT, and VBench as applicable. Source
versions and license notes are recorded in THIRD_PARTY_NOTICES.md and
docs/third_party_commits.md in the GitHub repository.