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visualpriors

The official implementation of visual priors from the paper Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies. Arxiv preprint 2018.

0.3.5
PyPI
Maintainers
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Visual Priors

Intro

This package contains the code for the paper:

Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies. Arxiv 2018/CoRL 2019. Alexander Sax, Jeffrey O. Zhang, Bradley Emi, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik.

  • For a fuller description and useful results and demos, and much more, see the website http://perceptual.actor.
  • For the code in this package, see https://github.com/alexsax/midlevel-reps/tree/visualpriors.
  • For the full code from the paper, dockers to reproduce experiments, and more, see https://github.com/alexsax/midlevel-reps.

Citation

If you find this repository or toolkit useful, then please cite:

@inproceedings{midLevelReps2018,
 title={Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies.},
 author={Alexander Sax and Jeffrey O. Zhang and Bradley Emi and Amir R. Zamir and Leonidas J. Guibas and Silvio Savarese and Jitendra Malik},
 year={2018},
}

Keywords

computer vision

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