phuselab / SSLD-face_recognition

Robust Single Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features

Home Page:https://www.mdpi.com/1424-8220/19/1/146

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Robust Single Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features

Vittorio Cuculo¹, Alessandro D'Amelio¹, Giuliano Grossi¹, Raffaella Lanzarotti¹, Jianyi Lin²
¹ PHuSe Lab - Dipartimento di Informatica, Università degli Studi di Milano
² Department of Mathematics, Khalifa University of Science and Technology

Paper Cuculo, V., D’Amelio, A., Grossi, G., Lanzarotti, R., & Lin, J. (2019). Robust single-sample face recognition by sparsity-driven sub-dictionary learning using deep features. Sensors, 19(1), 146.

https://www.mdpi.com/1424-8220/19/1/146

pipeline

Requirements

To execute the code, please make sure that the following packages are installed:

  • python 3.6.5
  • scikit-learn 0.20.0

Executing the demo

To launch the classification test on LFW-158 subset:

  1. Download the pre-processed data (~10GB unzipped):
./download_data.sh
  1. Run the following command:
python3 main.py

[...]

Number of images: 4165

Accuracy: 94.23769507803121%

Reference

If you use this code or data, please cite the paper:

@Article{s19010146,
AUTHOR = {Cuculo, Vittorio and D’Amelio, Alessandro and Grossi, Giuliano and Lanzarotti, Raffaella and Lin, Jianyi},
TITLE = {Robust Single-Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features},
JOURNAL = {Sensors},
VOLUME = {19},
YEAR = {2019},
NUMBER = {1},
ARTICLE-NUMBER = {146},
URL = {http://www.mdpi.com/1424-8220/19/1/146},
ISSN = {1424-8220},
DOI = {10.3390/s19010146}
}

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Quadro P6000 GPU used for this research.

About

Robust Single Sample Face Recognition by Sparsity-Driven Sub-Dictionary Learning Using Deep Features

https://www.mdpi.com/1424-8220/19/1/146

License:MIT License


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