4 papers
SAGA: Source Attribution of Generative AI Videos
Rohit Kundu, Vishal Mohanty, Hao Xiong +3
The proliferation of generative AI has led to hyper-realistic synthetic videos, escalating misuse risks and outstripping binary real/fake detectors. We introduce SAGA (Source Attri…
TruthLens: Visual Grounding for Universal DeepFake Reasoning
Rohit Kundu, Shan Jia, Vishal Mohanty +2
Detecting DeepFakes has become a crucial research area as the widespread use of AI image generators enables the effortless creation of face-manipulated and fully synthetic content,…
Towards a Universal Synthetic Video Detector: From Face or Background Manipulations to Fully AI-Generated Content
Rohit Kundu, Hao Xiong, Vishal Mohanty +2
Existing DeepFake detection techniques primarily focus on facial manipulations, such as face-swapping or lip-syncing. However, advancements in text-to-video (T2V) and image-to-vide…
Can DeepFake Speech be Reliably Detected?
Hongbin Liu, Youzheng Chen, Arun Narayanan +3
Recent advances in text-to-speech (TTS) systems, particularly those with voice cloning capabilities, have made voice impersonation readily accessible, raising ethical and legal con…