With various facial manipulation techniques arising, face forgery detection has drawn
growing attention due to security concerns. Previous works always formulate face forgery …

Current face forgery detection methods achieve high accuracy under the within-database
scenario where training and testing forgeries are synthesized by the same algorithm …

In this work, we propose a novel method to improve the generalization ability of CNN-based
face forgery detectors. Our method considers the feature anomalies of forged faces caused …

In this paper, we propose a domain-general model, termed learning-to-weight (LTW), that
guarantees face detection performance across multiple domains, particularly the target …

Face forgery detection is raising ever-increasing interest in computer vision since facial
manipulation technologies cause serious worries. Though recent works have reached …

With the rapid development of facial manipulation techniques, face forgery has received
considerable attention in digital media forensics due to security concerns. Most existing …

Face forgery detection is essential in combating malicious digital face attacks. Previous
methods mainly rely on prior expert knowledge to capture specific forgery clues, such as …

Existing face forgery detectors mainly focus on specific forgery patterns like noise
characteristics, local textures, or frequency statistics for forgery detection. This causes …

Beyond high accuracy, good interpretability is very critical to deploy a face forgery detection
model for visual content analysis. In this paper, we propose learning patch-channel …

Recently, Deepfake arises as a powerful tool to fool the existing real-world face detection
systems, which has received wide attention in both academia and society. Most existing …