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        "author": "Alexander Sax, Bradley Emi, Jeffrey Zhang, Amir R. Zamir, Silvio Savarese, Leonidas Guibas, Jitendra Malik",
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            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
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        "description": "# Visual Priors\n\n\n# Intro\nThis package contains the code for the paper:\n\n**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.\n\n- For a fuller description and useful results and demos, and much more, see the website [http://perceptual.actor](http://perceptual.actor).\n- For the code in this package, see [https://github.com/alexsax/midlevel-reps/tree/visualpriors](https://github.com/alexsax/midlevel-reps/tree/visualpriors).\n- 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).\n\n\n### Citation\nIf you find this repository or toolkit useful, then please cite:\n```\n@inproceedings{midLevelReps2018,\n\u2003title={Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies.},\n\u2003author={Alexander Sax and Bradley Emi and Amir R. Zamir and Leonidas J. Guibas and Silvio Savarese and Jitendra Malik},\n\u2003year={2018},\n}\n```",
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        "keywords": "computer vision,robotics,perception,midlevel,mid-level,reinforcement learning,machine learning,representation learning",
        "license": "MIT",
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        "name": "visualpriors",
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        "summary": "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.",
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