Metadata-Version: 2.4
Name: gaia2-pytorch
Version: 0.0.2
Summary: Gaia2 - Pytorch
Project-URL: Homepage, https://pypi.org/project/gaia2-pytorch/
Project-URL: Repository, https://github.com/lucidrains/gaia2-pytorch
Author-email: Phil Wang <lucidrains@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Phil Wang
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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License-File: LICENSE
Keywords: artificial intelligence,autonomous driving,deep learning,flow matching,transformers
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Requires-Dist: einops>=0.8.1
Requires-Dist: einx>=0.3.0
Requires-Dist: ema-pytorch
Requires-Dist: jaxtyping
Requires-Dist: torch>=2.4
Provides-Extra: examples
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Description-Content-Type: text/markdown

<img src="./gaia2.png" width="450px"></img>

## Gaia2 - Pytorch (wip)

Implementation of the world model architecture for the domain of self driving out of Wayve

Please let me know your thoughts of the paper [here](https://discord.gg/na5MQBUJqb), positive or negative, so I can gauge its significance / prioritize

## Citations

```bibtex
@article{Russell2025GAIA2AC,
    title   = {GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving},
    author  = {Lloyd Russell and Anthony Hu and Lorenzo Bertoni and George Fedoseev and Jamie Shotton and Elahe Arani and Gianluca Corrado},
    journal = {ArXiv},
    year    = {2025},
    volume  = {abs/2503.20523},
    url     = {https://api.semanticscholar.org/CorpusID:277321454}
}
```

```bibtex
@article{Rombach2021HighResolutionIS,
    title   = {High-Resolution Image Synthesis with Latent Diffusion Models},
    author  = {Robin Rombach and A. Blattmann and Dominik Lorenz and Patrick Esser and Bj{\"o}rn Ommer},
    journal = {2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year    = {2021},
    pages   = {10674-10685},
    url     = {https://api.semanticscholar.org/CorpusID:245335280}
}
```
