TransUNet for image forgery localization

Kedi Li; Lin Li; Qingyan Li

doi:10.1117/12.3008398

14 November 2023 TransUNet for image forgery localization

Kedi Li, Lin Li, Qingyan Li

Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129340P (2023) https://doi.org/10.1117/12.3008398
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China

Abstract

Image tampering can easily be used in illegal activities such as false propaganda, fake news and falsifying evidence in court which may have a negative impact on society. Therefore, we need to constantly update and improve the image tampering detection technology. TransUNet is an efficient model for medical image segmentation. This paper modified and migrated TransUNet which to image forgery localization, and conducted experiments on standard datasets to demonstrate the effectiveness of TransUNet. The findings shows that the proposed framework is superior to several existing forged area localization techniques.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kedi Li, Lin Li, and Qingyan Li "TransUNet for image forgery localization", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129340P (14 November 2023); https://doi.org/10.1117/12.3008398

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