Results 91 to 100 of about 1,097 (171)

Improving Fairness in Deepfake Detection

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Despite the development of effective deepfake detectors in recent years, recent studies have demonstrated that biases in the data used to train these detectors can lead to disparities in detection accuracy across different races and genders. This can result in different groups being unfairly targeted or excluded from detection, allowing undetected ...
Yan Ju, Shu Hu 0001, Shan Jia, George H. Chen, Siwei Lyu   +4 more
openaire   +2 more sources

Deepfake noise investigation and detection

Forensic Science International: Digital Investigation, 2022
Tianyi Wang 0006, Ming Liu, Wei Cao, Kam-Pui Chow   +3 more
openaire   +1 more source

Scaling Laws for Deepfake Detection

CoRR
This paper presents a systematic study of scaling laws for the deepfake detection task. Specifically, we analyze the model performance against the number of real image domains, deepfake generation methods, and training images. Since no existing dataset meets the scale requirements for this research, we construct ScaleDF, the largest dataset to date in ...
Wenhao Wang, Longqi Cai, Taihong Xiao, Yuxiao Wang 0001, Ming-Hsuan Yang 0001   +4 more
openaire   +2 more sources

A Unified Neural Framework for Real-Time Deepfake Detection Across Multimedia Modalities to Combat Misleading Content

IEEE Access
The rise of deepfake technology poses significant threats to the authenticity of content on social media. This research introduces Sach-AI, a pioneering framework for detecting various deepfakes in video, audio, and image data.
Ayan Sar, Subhangi Sati, Tanupriya Choudhury, Purvika Joshi, Roohi Sille, K. Srihari, Kritika Bansal   +6 more
doaj   +1 more source

A Multimodal Framework for Deepfake Detection

Journal of Electrical Systems
The rapid advancement of deepfake technology poses a significant threat to digital media integrity. Deepfakes, synthetic media created using AI, can convincingly alter videos and audio to misrepresent reality. This creates risks of misinformation, fraud, and severe implications for personal privacy and security.
Kashish Gandhi, Prutha Kulkarni, Taran Shah, Piyush Chaudhari, Meera Narvekar, Kranti Ghag   +5 more
openaire   +2 more sources

Deepfake Video Traceability and Authentication via Source Attribution

IET Biometrics
In recent years, deepfake videos have emerged as a significant threat to societal and cybersecurity landscapes. Artificial intelligence (AI) techniques are used to create convincing deepfakes. The main counter method is deepfake detection.
Canghai Shi, Minglei Qiao, Zhuang Li, Zahid Akhtar, Bin Wang, Meng Han, Tong Qiao   +6 more
doaj   +1 more source

Multiclass AI-Generated Deepfake Face Detection Using Patch-Wise Deep Learning Model

Computers
In response to the rapid advancements in facial manipulation technologies, particularly facilitated by Generative Adversarial Networks (GANs) and Stable Diffusion-based methods, this paper explores the critical issue of deepfake content creation.
Muhammad Asad Arshed, Shahzad Mumtaz, Muhammad Ibrahim, Christine Dewi, Muhammad Tanveer, Saeed Ahmed   +5 more
doaj   +1 more source

Deepfake detection with and without content warnings. [PDF]

R Soc Open Sci, 2023
Lewis A, Vu P, Duch RM, Chowdhury A.
europepmc   +1 more source

On the Generalization of Deep Learning Models in Video Deepfake Detection. [PDF]

J Imaging, 2023
Coccomini DA, Caldelli R, Falchi F, Gennaro C.   +3 more
europepmc   +1 more source

Local attention and long-distance interaction of rPPG for deepfake detection. [PDF]

Vis Comput, 2023
Wu J, Zhu Y, Jiang X, Liu Y, Lin J.
europepmc   +1 more source