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12 changes: 3 additions & 9 deletions README.md
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Crossnet, a cross-view supervised learning solution
Predicting Ground-Level Scene Layout from Aerial Imagery
========

This code is a tensorflow implementation of this paper, [Predicting Ground-Level Scene Layout from Aerial Imagery](http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhai_Predicting_Ground-Level_Scene_CVPR_2017_paper.pdf).

And you are welcome to visit our [Project Page](http://cs.uky.edu/~ted/research/crossview/)
This code is a TensorFlow implementation of this CVPR 2017 paper: [Predicting Ground-Level Scene Layout from Aerial Imagery](http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhai_Predicting_Ground-Level_Scene_CVPR_2017_paper.pdf).

Dependencies
------------
Expand All @@ -22,9 +20,5 @@ $ python main.py --is_training=False
```
Data
------------
This repo only contains some example data for training, the whole dataset can be found in [this link](https://drive.google.com/open?id=0BzvmHzyo_zCAX3I4VG1mWnhmcGc).
You would have to edit the dataset path in main.py in order to use it.
This repository only contains example data for training; the full dataset can be requested from [this link]([https://drive.google.com/open?id=0BzvmHzyo_zCAX3I4VG1mWnhmcGc](https://mvrl.cse.wustl.edu/datasets/cvusa/). You would have to edit the dataset path in main.py in order to use it.

Note
------------
We plan to release evaluation code soon.