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README.md
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# MoSE3: Learning World-Space SE(3) at Every Pixel
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[Paper](https://arxiv.org/abs/2610.03716) | [Project page](https://mose3-tracker.github.io/)
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MoSE3 predicts dense SE(3) motion from a monocular RGB video: a 6-DoF rigid transform for every pixel
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of a query frame, in world space. On top of a frozen [π³](https://github.com/yyfz/Pi3) geometry branch,
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model = MoSE3.from_pretrained("JoannaCCCCCC/MoSE3", strict=True).cuda().eval()
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```
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The code repository has the full inference and visualization scripts.
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## License
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# MoSE3: Learning World-Space SE(3) at Every Pixel
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[Paper](https://arxiv.org/abs/2610.03716) | [Project page](https://mose3-tracker.github.io/) | [Code](https://github.com/mose3-tracker/MoSE3)
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MoSE3 predicts dense SE(3) motion from a monocular RGB video: a 6-DoF rigid transform for every pixel
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of a query frame, in world space. On top of a frozen [π³](https://github.com/yyfz/Pi3) geometry branch,
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model = MoSE3.from_pretrained("JoannaCCCCCC/MoSE3", strict=True).cuda().eval()
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```
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The [code repository](https://github.com/mose3-tracker/MoSE3) has the full inference and visualization scripts.
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## License
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