Recent advancements in deep learning generative models have raised concerns as they
can create highly convincing counterfeit images and videos. This poses a threat to people's …

With the progression of deep-learning techniques, digital media recording and synthesis
media generation have become exceptionally easy. Due to open access of user-friendly …

Generative deep learning techniques have invaded the public discourse recently. Despite
the advantages, the applications to disinformation are concerning as the counter-measures …

With the development of generative models, abused Deepfakes have aroused public
concerns. As a defense mechanism, face forgery detection methods have been intensively …

With the recent rise of realistic face manipulation methods, building robust face tampering
detection methods has become more critical than ever before. Several research works have …

Detecting digital face manipulation in images and video has attracted extensive attention
due to the potential risk to public trust. To counteract the malicious usage of such …

Deep fake technology has emerged as a double-edged sword in the digital world. While it
holds potential for legitimate uses, it can also be exploited to manipulate video content …

With the large chunks of social media data being created daily and the parallel rise of
realistic multimedia tampering methods, detecting and localising tampering in images and …

In recent years, image and video manipulations with Deepfake have become a severe
concern for security and society. Many detection models and datasets have been proposed …

Recently, the higher availability of multimedia content on social websites, together with
lightweight deep learning (DL) empowered tools like Generative Adversarial Networks …