Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detection-Reference-Cited by-同舟云学术

Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detection

Published:2024 Issue: Volume:19 Page:1168-1182
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Luo Anwei¹^ORCID,Kong Chenqi²^ORCID,Huang Jiwu³^ORCID,Hu Yongjian⁴^ORCID,Kang Xiangui¹^ORCID,Kot Alex C.⁵^ORCID

Affiliation:

1. Guangdong Key Laboratory of Information Security, and School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

2. School of Electrical and Electrics Engineering, Nanyang Technological University, Jurong West, Singapore

3. Guangdong Key Laboratory of Intelligent Information Processing, and the National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China

4. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China

5. School of Electrical and Electronic Engineering, Nanyang Technology University, 50 Nanyang Ave, Singapore

Funder

NSFC

Science and Technology Foundation of Guangzhou Huangpu Development District

Rapid-Rich Object Search (ROSE) Laboratory, Nanyang Technological University, Singapore

China–Singapore International Joint Research Institute

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/10319981/10315169.pdf?arnumber=10315169

Reference98 articles.

1. Protecting Celebrities from DeepFake with Identity Consistency Transformer

2. Thinking in frequency: Face forgery detection by mining frequency-aware clues;qian;Proc Eur Conf Comput Vis,2020

3. End-to-End Reconstruction-Classification Learning for Face Forgery Detection

4. Improving Generalization by Commonality Learning in Face Forgery Detection

5. Enhancing General Face Forgery Detection via Vision Transformer with Low-Rank Adaptation

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