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Source code for the paper "An Adaptive Affinity Graph with Subspace Pursuit for Natural Image Segmentation".

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AASP-Graph

Source code for the paper "An Adaptive Affinity Graph with Subspace Pursuit for Natural Image Segmentation". The AASP-Graph paper can be found here.

AASP-Graph is modified from the offcial GL-Graph implementation.

Requirements

The code requires the version of Matlab2018a, Ubuntu 16.04.

Data

The BSDS300 dataset and predata (extracted features) can be downloaded from GL-Graph and place them in BSD/ and bsd_300_feat/ folder, respectively.

Demo

Run the demo demo_AASP_BSDS300.m.

Results

The detailed results can be found in BSDS300_evaluation.txt. More relevant results of natural image segmentation can be found in our projects.

Citing

If you find this repository useful in your research, please consider citing:

@INPROCEEDINGS{AASP-Graph,  
  author={Y. {Zhang} and H. {Zhang} and Y. {Guo} and K. {Lin} and J. {He}},  
  booktitle={IEEE International Conference on Multimedia and Expo (ICME)},   
  title={An Adaptive Affinity Graph with Subspace Pursuit for Natural Image Segmentation},   
  year={2019},  
  pages={802-807},}

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Source code for the paper "An Adaptive Affinity Graph with Subspace Pursuit for Natural Image Segmentation".

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