BNF Globalization Code (CVPR 2016)

Last update: Apr 15, 2022

Related tags

Computer Vision BNF_globalization

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

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