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Boundary Neural Fields Globalization

This is the code for Boundary Neural Fields globalization method. The technical report of the method can be found at http://arxiv.org/pdf/1511.02674v1.pdf

If you use this software please cite our CVPR 2016 paper:

@InProceedings{gberta_2016_CVPR,<br /> author = {Gedas Bertasius and Jianbo Shi and Lorenzo Torresani},<br /> title = {Semantic Segmentation with Boundary Neural Fields},<br /> booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},<br /> month = {June},<br /> year = {2016}<br /> }

Installation

1. VL Feat

   Compile the VL Feat library in the folder 'libs/'

2. Normalized Cuts

   Compile Normalized Cuts code in the directory 'Ncuts_9/''

Usage

To use BNF method with the boundary based affinities, check out the files 'BNF_binary_class_edge_affinity_demo.m' and 'BNF_multi_class_edge_affinity_demo.m' for binary and multi class segmentations respectively. If the boundaries are not available, you can use the demos 'BNF_binary_class_RGB_affinity_demo.m' and 'BNF_multi_class_RGB_affinity_demo.m', which perform our globalization technique using the RGB color affinities.

Notes

This version of the code is slightly different than the one presented in the technical report.