Fake Face Detection Based on Fusion of Spatial Texture and High-Frequency Noise

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Zhang, Dengyong;Qi, Feifan;Chen, Jiahao;Chen, Jiaxin;Gong, Rongrong;...

通讯作者：

Zhang, DY

作者机构：

[Chen, Jiaxin; Qi, Feifan; Chen, Jiahao; Zhang, Dengyong] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Hunan Prov Key Lab Intelligent Proc Big Data Trans, Changsha 410004, Peoples R China.

[Chen, Jiaxin; Qi, Feifan; Chen, Jiahao; Zhang, Dengyong] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410004, Peoples R China.

[Gong, Rongrong] Changsha Social Work Coll, Changsha 410004, Peoples R China.

[Tian, Yuehong] Changkuangao Beijing Technol Co Ltd, Beijing 101100, Peoples R China.

[Zhang, Lebing] Huaihua Univ, Sch Comp & Artificial Intelligence, Huaihua 418000, Peoples R China.

通讯机构：

[Zhang, DY ] C

Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Hunan Prov Key Lab Intelligent Proc Big Data Trans, Changsha 410004, Peoples R China.

Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410004, Peoples R China.

语种：

英文

关键词：

Convolutional neural networks;Distribution transformers;Face recognition;Image texture;Steganography;Deepfake detection;Detection methods;Facial images;High-frequency noise;Image forensics;Mix attention;Spatial domains;Spatial texture;Steganalysis;Steganalyze rich model;Convolution

期刊：

电子学报(英文)

ISSN：

1022-4653

年：

2025

卷：

期：

页码：

212-221

DOI：

10.23919/cje.2023.00.342

基金类别：

National Natural Science Foundation of China, NSFC, (62172059) National Natural Science Foundation of China, NSFC Scientific Research Foundation of Hunan Provincial Education Department, (22A0200) Scientific Research Foundation of Hunan Provincial Education Department Scientific Research Fund of Hunan Provincial Natural Science Foundation, (2023JJ60257)

机构署名：

本校为第一且通讯机构

院系归属：

计算机与通信工程学院

摘要：

The rapid development of the Internet has led to the widespread dissemination of manipulated facial images, significantly impacting people's daily lives. With the continuous advancement of Deepfake technology, the generated counterfeit facial images have become increasingly challenging to distinguish. There is an urgent need for a more robust and convincing detection method. Current detection methods mainly operate in the spatial domain and transform the spatial domain into other domains for analysis. With the emergence of transformers, some researchers have also combined traditional convoluti...

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Fake Face Detection Based on Fusion of Spatial Texture and High-Frequency Noise

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