SEDN: A Spatiotemporal Encoder-Decoder Network for End-to-End Object Removal Forgery Detection in High-Resolution Videos

With the growing popularity of high-resolution (HR) video and the continuous growth of network bandwidth, the challenge of object removal detection in HR videos has attracted significant attention. Expert forgers leverage the rich detail in HR videos for meticulous pixel manipulation and apply sophi...

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Vydané v:	IEEE transactions on multimedia Ročník 27; s. 2503 - 2515
Hlavní autori:	Xiong, Lizhi, Ding, Linsen, Cao, Mengqi, Xia, Zhihua, Shi, Yun-Qing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2025
Predmet:	3D convolution Accuracy Data mining Feature extraction Forgery hybrid encoder-decoder model Location awareness Object detection Object removal forgery detection spatiotemporal localization Spatiotemporal phenomena Transformers Transforms Vectors video passive forensics
ISSN:	1520-9210, 1941-0077
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