# 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](http://perceptual.actor).
For the code in this package, see [https://github.com/alexsax/midlevel-reps/tree/visualpriors](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](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}, } `
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Release files for visualpriors 0.3.5
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| File | Size | Uploaded | |
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Release files / visualpriors-0.3.5.tar.gz
| Download URL | visualpriors-0.3.5.tar.gz |
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