TransU²-Net: A Hybrid Transformer Architecture for Image Splicing Forgery Detection

In recent years, various convolutional neural network (CNN) based frameworks have been presented to detect forged regions in images. However, most of the existing models can not obtain satisfactory performance due to tampered areas with various sizes, especially for objects with large-scale. In orde...

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Bibliografische Detailangaben

Hauptverfasser:	Caiping Yan, Shuyuan Li, Hong Li
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2023-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Image splicing forgery detection tampered region localization convolutional neural network self-attention cross-attention
Online-Zugang:	https://ieeexplore.ieee.org/document/10090941/
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