This is project page for the paper title "An Inference Algorithm for Multi-Label MRF-MAP Problems with Clique Size 100" published in ECCV 2020. The paper is available at link: https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650256.pdf. The proposed method is an inference algorithm for solving multi-label MRF-MAP problem. Please cite our paper if you find this code useful.
@inproceedings{shanu2020inference,
title={An Inference Algorithm for Multi-Label MRF-MAP Problems with Clique Size 100},
author={Shanu, Ishant and Bharti, Siddhant and Arora, Chetan and Maheshwari, SN},
booktitle={European Conference on Computer Vision},
pages={257--274},
year={2020},
organization={Springer}
}
- Download the code from this repo.
- Download PASCAL VOC12 dataset from http://host.robots.ox.ac.uk/pascal/VOC/voc2012/#data.
Please run data_preprocess/runslic.py and data_preprocess/get_unary.py for generating and storing the clique and unary information in the required format.
This project can be run on Visual Studio 2017 with the following packges installed. Please download VS2017 from https://visualstudio.microsoft.com/vs/older-downloads/.
- Please download and setup Eigen3 as per information given on the link: https://phylogeny.uconn.edu/tutorial-v2/part-1-ide-project-v2/setting-up-the-eigen-library-v2/.
- Similarly download and setup openCV package as per instructions given at https://www.opencv-srf.com/2017/11/install-opencv-with-visual-studio.html.