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Found 5 papers, 2 papers with code
Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection
We propose to train detectors using only pristine images injecting in part of them crafted frequency patterns, simulating the effects of various deepfake generation techniques without being specific to any.
Deepfake detection by exploiting surface anomalies: the SurFake approach
In particular, when an image (video) is captured the overall geometry of the scene (e. g. surfaces) and the acquisition process (e. g. illumination) determine a univocal environment that is directly represented by the image pixel values; all these intrinsic relations are possibly changed by the deepfake generation process.
Optical identification using physical unclonable functions
In this work, the concept of optical identification (OI) based on physical unclonable functions is introduced for the first time, to our knowledge, in optical communication systems and networks.
MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection
In this paper, we introduce MINTIME, a video deepfake detection approach that captures spatial and temporal anomalies and handles instances of multiple people in the same video and variations in face sizes.
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Cross-Forgery Analysis of Vision Transformers and CNNs for Deepfake Image Detection
Deepfake Generation Techniques are evolving at a rapid pace, making it possible to create realistic manipulated images and videos and endangering the serenity of modern society.
