Nowadays, numerous synthesized images and videos generated by facial manipulated
techniques have become an emerging problem, which promotes facial manipulation …

Deepfake detection refers to detecting artificially generated or edited faces in images or
videos, which plays an essential role in visual information security. Despite promising …

Resizing input face images of arbitrary sizes to a uniform size is an essential preprocessing
to satisfy the architectural requirements of face forgery detectors. In this letter, we reveal an …

Deepfake has emerged for several years, yet efficient detection techniques could generalize
over different manipulation methods require further research. While current image-level …

Recently, deep face forgery detection has been attracting considerable attentions, due to the
potential security consequences induced by this type of forgeries. Unfortunately, the existing …

Deep generative models have demonstrated impressive performance in various computer
vision applications, including image synthesis, video generation, and medical analysis …

Many existing face forgery detection methods primarily revolve around learning general
representations on predefined datasets and subsequently crossing these static …

Images that are manipulated are prevalent and are on the spike because of the
advancement in deep convolutional neural networks (CNNs) techniques. There have been …

Classifier fusion is established as an effective methodology for boosting performance in
different settings and one-class classification is no exception. In this study, we consider the …

In recent years, AI-driven advancements have resulted in increasingly sophisticated face
forgery techniques, posing a challenge in distinguishing genuine images from manipulated …