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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Veröffentlicht in:	IEEE transactions on multimedia Jg. 27; S. 2503 - 2515
Hauptverfasser:	Xiong, Lizhi, Ding, Linsen, Cao, Mengqi, Xia, Zhihua, Shi, Yun-Qing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	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
Online-Zugang:	Volltext
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