Publication detail

Facial Image Reconstruction and its Influence to Face Recognition

PLEŠKO, F. GOLDMANN, T. MALINKA, K.

Original Title

Facial Image Reconstruction and its Influence to Face Recognition

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper focuses on reconstructing damaged facial images using GAN neural networks. In addition, the effect of generating the missing part of the face on face recognition is investigated. The main objective of this work is to observe whether it is possible to increase the accuracy of face recognition by generating missing parts while maintaining a low false accept rate (FAR). A new model for generating the missing parts of a face has been proposed. For face-based recognition, state-of-the-art solutions from the DeepFace library and the QMagFace solution have been used.

Keywords

face recognition, neural network, face reconstruction, generativní adversariální síť, SFace, ArcFace, QMagFace

Authors

PLEŠKO, F.; GOLDMANN, T.; MALINKA, K.

Released

20. 8. 2023

Publisher

Society for Informatics

Location

Darmstadt

ISBN

979-8-3503-3655-9

Book

2023 International Conference of the Biometrics Special Interest Group (BIOSIG)

Pages from

1

Pages to

4

Pages count

5

URL

https://ieeexplore.ieee.org/document/10346000

BibTex

@inproceedings{BUT186943,
  author="Filip {Pleško} and Tomáš {Goldmann} and Kamil {Malinka}",
  title="Facial Image Reconstruction and its Influence to Face Recognition",
  booktitle="2023 International Conference of the Biometrics Special Interest Group (BIOSIG)",
  year="2023",
  pages="1--4",
  publisher="Society for Informatics",
  address="Darmstadt",
  doi="10.1109/BIOSIG58226.2023",
  isbn="979-8-3503-3655-9",
  url="https://ieeexplore.ieee.org/document/10346000"
}