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README.md

README.md

Unsupervised image matching and object discovery as optimization

Huy V. Vo, Francis Bach, Minsu Cho, Kai Han, Yann LeCun, Patrick Pérez, Jean Ponce - CVPR 2019

Getting started

The code is written and tested with Matlab 2017a. Modifications might be necessary to run it with other versions of Matlab.

Installing

git clone https://github.com/vohuy93/UODOptim.git
cd UODOptim

Dependencies

You need to download the code for generating region proposals with randomized Prim's algorithm and put it in the UODOptim/ folder

git clone https://github.com/smanenfr/rp.git

then run

cd rp; matlab -r "setup"

Running the tests

The main script for testing the code on VOC_6x2 is scripts/run_UOD.m. In a terminal, from the UODOptim folder, run

cd scripts; matlab -r "run_UOD"

Citations

@INPROCEEDINGS{Vo19UOD,
  title     = {Unsupervised image matching and object discovery as optimization},
  author    = {Vo, Huy V. and Bach, Francis and Cho, Minsu and Han, Kai and LeCun, Yann and P{\'e}rez, Patrick and Ponce, Jean},
  booktitle = {CVPR},
  year      = {2019}
}

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

The code for Probabilistic Hough Matching (PHM) algorithm is taken from the project page of the paper "Unsupervised Object Discovery and Localization in the Wild".

This work was supported in part by the Inria/NYU collaboration agreement, the Louis Vuitton/ENS chair on artificial intellgence and the EPSRC Programme Grant Seebibyte EP/M013774/1.

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