BNF Globalization Code (CVPR 2016)

Last update: Apr 15, 2022

Related tags

Overview

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

Installation

VL Feat

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

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Comments

Weight Magnitude

Hi and thanks for the paper about BNF

I am very interested in the edge detector. You have used in your paper the Weight Magnitudes, but I didn't found the explanation, how they are calculated or where they can be found. Can you give me a hint, please?

Thanks a lot André

opened by Apeke 4

BNF Globalization Code (CVPR 2016)

Related tags

Overview

Boundary Neural Fields Globalization

Installation

Usage

Notes

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Comments

Weight Magnitude

Owner

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