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 …

Automatic medical image segmentation has made great progress owing to powerful deep
representation learning. Inspired by the success of self-attention mechanism in transformer …

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 …

In this paper, we analyse the generalization ability of binary classifiers for the task of
deepfake detection. We find that the stumbling block to their generalization is caused by the …

Recent advances in image editing techniques have posed serious challenges to the
trustworthiness of multimedia data, which drives the research of image tampering detection …

This paper proposes a self-supervised approach to learn universal facial representations
from videos, that can transfer across a variety of facial analysis tasks such as Facial Attribute …

Recently, deepfakes have raised severe concerns about the authenticity of online media.
Prior works for deepfake detection have made many efforts to capture the intra-modal …

Deepfake detection remains a challenging task due to the difficulty of generalizing to new
types of forgeries. This problem primarily stems from the overfitting of existing detection …

With the springing up of face synthesis techniques, it is prominent in need to develop
powerful face forgery detection methods due to security concerns. Some existing methods …

In recent years, face forgery detectors have aroused great interest and achieved impressive
performance, but they are still struggling with generalization and robustness. In this work, we …