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Code for Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies. Arxiv preprint 2018. Alexander Sax, Bradley Emi, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik.

License: MIT License

visual-prior's Introduction

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 preprint 2018. Alexander Sax, 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 for this repository, see https://github.com/alexsax/visual-prior.
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 Bradley Emi and Amir R. Zamir and Leonidas J. Guibas and Silvio Savarese and Jitendra Malik},
 year={2018},
}

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visual-prior's Issues

incompatible net architecture when loading states_dict

Hi,

I found there are some errors when loading some of the pretrained model. Apparently, it's because the net architecture used for training is different with the net used for reproduction, which refers to the encoder and decoder defined in this repo. We have the same architecture for all the tasks here (except for the output layer). But the trained model use different net architectures for some of the tasks. So maybe it is better to give a clear instruction about which task is supported by this repo.
Besides, I found this repo is pretty similar to the task bank module in the taskonomy repo. Is there any difference between them?

Thanks

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