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Fleurrr/
A2World-World-Model

Name: A2World-World-Model
Rating: 2.5 (228 reviews)

action-conditioned-video

image-to-video

nvidia/Cosmos-Predict2-2B-Video2World

finetune

other

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A2World World Model

A2World is a multi-view action-conditioned diffusion world model trained to predict future robot observations from initial camera observations and a 20-step action chunk. A2World-sim adds pose-guided visual history and autoregressive rollout support.

Variants

a2world-pretrained.pt: heterogeneous robot-data pretrained A2World checkpoint.
a2world-libero.pt: history-aware A2World-sim checkpoint adapted on LIBERO.

Both released files use EMA weights, the standard net.* inference prefix, and BF16 storage compatible with the public rollout pipeline.

Base Model and License

The checkpoints are derivative models of nvidia/Cosmos-Predict2-2B-Video2World and are governed by the NVIDIA Open Model License included in this repository. Source code is separately available under Apache-2.0.

Intended Use

Multi-view action-conditioned robot video prediction.
Open-loop and chunk-wise autoregressive world-model rollouts.
LIBERO learned-simulator research and downstream adaptation.
Research on transferable robot dynamics priors.

Limitations

Generated rollouts may hallucinate geometry, contact, object state, or task success.
Autoregressive errors accumulate over long horizons.
Camera identity and action semantics must match the selected embeddings and preprocessing.
The model is not a certified simulator and must not replace real-robot safety validation.

Citation

bibtex

@inproceedings{huang2026a2world,
    title={Learning Transferable Dynamics Priors from Action to World Modeling},
    author={Huang, Ze and Zhang, Jiahui and Liu, Hairuo and Zhang, Chenxi and Cheng, Ran and Zhang, Li},
    booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
    year={2026},
}

Fleurrr/A2World-World-Model