96 citations · 355 across the 27 of their papers we have counts for
10 papers · 1 filter
DA-FDFtNet: Dual Attention Fake Detection Fine-tuning Network to Detect Various AI-Generated Fake Images
Young Oh Bang, Simon S. Woo
Due to the advancement of Generative Adversarial Networks (GAN), Autoencoders, and other AI technologies, it has been much easier to create fake images such as "Deepfakes". More re…
Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images
Binh M. Le, Simon S. Woo
The rapid progression of Generative Adversarial Networks (GANs) has raised a concern of their misuse for malicious purposes, especially in creating fake face images. Although many…
ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images
Binh M. Le, Simon S. Woo
Despite significant advancements of deep learning-based forgery detectors for distinguishing manipulated deepfake images, most detection approaches suffer from moderate to signific…
Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors
Hasam Khalid, Minha Kim, Shahroz Tariq +1
Significant advancements made in the generation of deepfakes have caused security and privacy issues. Attackers can easily impersonate a person's identity in an image by replacing…
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
Minha Kim, Shahroz Tariq, Simon S. Woo
Over the last few decades, artificial intelligence research has made tremendous strides, but it still heavily relies on fixed datasets in stationary environments. Continual learnin…
FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
Hasam Khalid, Shahroz Tariq, Minha Kim +1
While the significant advancements have made in the generation of deepfakes using deep learning technologies, its misuse is a well-known issue now. Deepfakes can cause severe secur…