Detail publikace

Facial Image Reconstruction and its Influence to Face Recognition

PLEŠKO, F. GOLDMANN, T. MALINKA, K.

Originální název

Facial Image Reconstruction and its Influence to Face Recognition

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

PLEŠKO, F.; GOLDMANN, T.; MALINKA, K.

Vydáno

20. 8. 2023

Nakladatel

Society for Informatics

Místo

Darmstadt

ISBN

979-8-3503-3655-9

Kniha

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

Strany od

1

Strany do

4

Strany počet

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"
}