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14 changes: 10 additions & 4 deletions README.md
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# R\*CNN

[![Join the chat at https://gitter.im/gkioxari/RstarCNN](https://badges.gitter.im/gkioxari/RstarCNN.svg)](https://gitter.im/gkioxari/RstarCNN?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
Source code for R\*CNN, created by Georgia Gkioxari at UC Berkeley.

### Introduction
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Download the data from [here](http://www.cs.berkeley.edu/~gkioxari/RstarCNN/BAPD.tar.gz) and place them inside the `$ROOT/data` directory

3. Reference models
3. Stanford 40 Dataset

Download the data from [here](http://www.cs.berkeley.edu/~gkioxari/RstarCNN/Stanford40.tar.gz) and place them inside `$ROOT/data` directory. R*CNN achieves 90.85% on the test set (trained models provided in 5)

4. Reference models

Download the VGG16 reference model trained on ImageNet from [here](http://www.cs.berkeley.edu/~gkioxari/RstarCNN/reference_models.tar.gz)
Download the VGG16 reference model trained on ImageNet from [here](http://www.cs.berkeley.edu/~gkioxari/RstarCNN/reference_models.tar.gz) (500M)

4. Trained models
5. Trained models

Download the models as described in the paper from [here](http://www.cs.berkeley.edu/~gkioxari/RstarCNN/trained_models.tar.gz)
Download the models as described in the paper from [here](http://www.cs.berkeley.edu/~gkioxari/RstarCNN/trained_models.tar.gz) (3.6G)



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