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Found 12 papers, 2 papers with code
Beyond Deepfake Images: Detecting AI-Generated Videos
Recent advances in generative AI have led to the development of techniques to generate visually realistic synthetic video.
E3: Ensemble of Expert Embedders for Adapting Synthetic Image Detectors to New Generators Using Limited Data
To address these issues, we introduce the Ensemble of Expert Embedders (E3), a novel continual learning framework for updating synthetic image detectors.
Open Set Synthetic Image Source Attribution
To address this new threat, researchers have developed multiple algorithms to detect synthetic images and identify their source generators.
Comprehensive Dataset of Synthetic and Manipulated Overhead Imagery for Development and Evaluation of Forensic Tools
We present a first of its kind dataset of overhead imagery for development and evaluation of forensic tools.
VideoFACT: Detecting Video Forgeries Using Attention, Scene Context, and Forensic Traces
While existing forensic networks have demonstrated strong performance on image forgeries, recent results reported on the Adobe VideoSham dataset show that these networks fail to identify fake content in videos.
Making Generated Images Hard To Spot: A Transferable Attack On Synthetic Image Detectors
Visually realistic GAN-generated images have recently emerged as an important misinformation threat.
Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers
In this paper, we propose new defenses that can protect against multi-sticker attacks.
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs
Understanding the transferability of adversarial attacks, i. e. an attacks ability to attack a different CNN than the one it was trained against, has important implications for designing CNNs that are resistant to attacks.
A Transferable Anti-Forensic Attack on Forensic CNNs Using A Generative Adversarial Network
In this paper, we propose a new anti-forensic attack framework designed to remove forensic traces left by a variety of manipulation operations.
Exposing Fake Images with Forensic Similarity Graphs
We propose new image forgery detection and localization algorithms by recasting these problems as graph-based community detection problems.
Forensic Similarity for Digital Images
In this paper we introduce a new digital image forensics approach called forensic similarity, which determines whether two image patches contain the same forensic trace or different forensic traces.
Constrained Convolutional Neural Networks: A New Approach Towards General Purpose Image Manipulation Detection
Furthermore, forensic analysts need ‘general purpose’ forensic algorithms capable of detecting multiple different image manipulations.
