The Library
Data-agnostic face image synthesis detection using Bayesian CNNs
Tools
Leyva, Roberto, Sanchez Silva, Victor, Epiphaniou, Gregory and Maple, Carsten (2024) Data-agnostic face image synthesis detection using Bayesian CNNs. Pattern Recognition Letters . doi:10.1016/j.patrec.2024.04.008 ISSN 0167-8655.
|
PDF
1-s2.0-S0167865524001090-main.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1073Kb) | Preview |
|
PDF
WRAP-data-agnostic-face-image-synthesis-detection-using-Bayesian-CNNs-2024.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (846Kb) |
Official URL: https://doi.org/10.1016/j.patrec.2024.04.008
Abstract
Face image synthesis detection is considerably gaining attention because of the potential negative impact on society that this type of synthetic data brings. In this paper, we propose a data-agnostic solution to detect the face image synthesis process. Specifically, our solution is based on an anomaly detection framework that requires only real data to learn the inference process. It is therefore data-agnostic in the sense that it requires no synthetic face images. The solution uses the posterior probability with respect to the reference data to determine if new samples are synthetic or not. Our evaluation results using different synthesizers show that our solution is very competitive against the state-of-the-art, which requires synthetic data for training.
Item Type: | Journal Article | ||||||
---|---|---|---|---|---|---|---|
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||
Journal or Publication Title: | Pattern Recognition Letters | ||||||
Publisher: | Elsevier BV | ||||||
ISSN: | 0167-8655 | ||||||
Official Date: | 30 April 2024 | ||||||
Dates: |
|
||||||
DOI: | 10.1016/j.patrec.2024.04.008 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 29 January 2024 | ||||||
Date of first compliant Open Access: | 9 May 2024 | ||||||
Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year