Advancements in deep learning techniques and the availability of free, large databases
have made it possible, even for non-technical people, to either manipulate or generate …

The rapid development of deep learning models that can produce and synthesize hyper-
realistic videos are known as DeepFakes. Moreover, the growth of forgery data has …

Over the past several years, to solve the problem of malicious abuse of facial manipulation
technology, face manipulation detection has obtained considerable attention. Although …

Recently almost all the mainstream deepfake detection methods use Convolutional Neural
Networks (CNN) as their backbone. However, due to the overreliance on local texture …

Due to the successful development of deep image generation technology, visual data
forgery detection would play a more important role in social and economic security. Existing …

The challenge of generalization in face forgery detection has become increasingly
prominent as manipulation techniques continue to evolve. Although recent image blending …

Face forgery detection (FFD) on digital images has become increasingly challenging with
the proliferation of sophisticated manipulation techniques. In this study, we propose a novel …

The reliability of remote identity-proofing systems (ie, electronic Know Your Customer, or
eKYC, systems) is challenged by the development of deepfake generation tools, which can …

Due to the security issues caused by face synthesis technology, face forgery detection has
received considerable attention. Therefore, there is an increasing necessity to develop …

Deepfakes have posed a significant challenge to digital forensics, and there is an increasing
need for high accuracy deepfake (DF) detection models in real-world scenarios. This …