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README.md

              ###################################################################
              #                                                                 #
              #    Deep Sketch Project                                          #
              #    Xiong Duan (hgysdx@163.com)                                  #
              #                                                                 #
              ###################################################################

Deepsketch

This code is incomplete corresponding to the paper, see more in http://dx.doi.org/10.1016/j.neucom.2016.04.046.

New version can be downloaded in https://github.com/XiongDuan/deepsketch.

If you use this demo in your project, we appreciate it if you cite an appropriate subset of our paper:

@article{wang2016deep, title={Deep Sketch Feature for Cross-domain Image Retrieval}, author={Wang, Xinggang and Duan, Xiong and Bai, Xiang}, journal={Neurocomputing}, year={2016}, publisher={Elsevier} }

The step of using deepsketch demo code.

  1. dataset.

    The skecth dataset can be downloaded in http://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/. And the corresponding image dataset can be downloaded in http://pan.baidu.com/s/1eSHfRdK

  2. toolbox.

    This project need download Piotr's Matlab Toolbox (https://pdollar.github.io/toolbox/), edgebox-toolbox(https://github.com/pdollar/edges) and caffe(https://github.com/BVLC/caffe) to support. For the windows-caffe, you can setup your environment by using(https://github.com/happynear/caffe-windows ).

  3. put the deepsketch, Piotr's Matlab Toolbox and edgebox-toolbox in caffe-windows-master\matlab.

    Then get in the dir deepsketch and edit deepsketch.m in your matlab wrapper and change all the paths in the code.

  4. run deepsketch.m if there is no error.

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This code is incomplete corresponding to the paper, see more in http://dx.doi.org/10.1016/j.neucom.2016.04.046

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