Although effective deepfake detection models have been developed in recent years recent
studies have revealed that these models can result in unfair performance disparities among …

The rapid advancement of Large AI Models (LAIMs), particularly diffusion models and large
language models, has marked a new era where AI-generated multimedia is increasingly …

Methods that can generate synthetic speech which is perceptually indistinguishable from
speech recorded by a human speaker are easily available. Several incidents report misuse …

DeepFake, an AI technology for creating facial forgeries, has garnered global attention.
Amid such circumstances, forensics researchers focus on developing defensive algorithms …

In the realm of medical imaging, particularly for COVID-19 detection, deep learning models
face substantial challenges such as the necessity for extensive computational resources, the …

Human affective behavior analysis aims to delve into human expressions and behaviors to
deepen our understanding of human emotions. Basic expression categories (EXPR) and …

Supervised learning models are challenged by the intrinsic complexities of training data
such as outliers and minority subpopulations and intentional attacks at inference time with …

This paper proposes a new adaptive blind watermarking technology for deepfake detection,
which can embed deepfake detection information into the image and verify the image's …

Diffusion models (DMs) have revolutionized image generation, producing high-quality
images with applications spanning various fields. However, their ability to create hyper …

Recent studies on deepfake detection have achieved promising results when training and
testing faces are from the same dataset. However, their results severely degrade when …