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Code for the project "MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos"

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MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos

arXiv 2024

Zhengqi Li1, Richard Tucker1, Forrester Cole1, Qianqian Wang1,2, Linyi Jin1,3, Vickie Ye2, Angjoo Kanazawa2, Aleksander Holynski1,2, Noah Snavely1,

1Google DeepMind, 2UC Berkeley, 3University of Michigan

TL;DR: MegaSaM estimates cameras and dense structure, quickly and accurately, from any static or dynamic video.


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Citation

 @article{li2024_MegaSaM,
  title     = {{MegaSaM}: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos},
  author    = {Li, Zhengqi and Tucker, Richard and Cole, Forrester and Wang, Qianqian and Jin, Linyi and Ye, Vickie and Kanazawa, Angjoo and Holynski, Aleksander and Snavely, Noah},
  journal   = {arXiv preprint},
  year      = {2024}
}

Acknowledgment

Thanks to Rick Szeliski, Peter Hedman, Andrew Liu, Boyang Deng, and Lucy Chai for helpful proofreading, comments, and discussions.

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Code for the project "MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos"

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