visualpriors 0.3.5

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.

# 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}, } `