DFAD23
* *DeepFake Analysis and Detection
* Attending Generalizability in Course of Deep Fake Detection by Exploring Multi-task Learning
* Comprehensive Framework for Evaluating Deepfake Generators: Dataset, Metrics Performance, and Comparative Analysis, A
* Deepfakes Signatures Detection in the Handcrafted Features Space
* Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality
* FIVA: Facial Image and Video Anonymization and Anonymization Defense
* Interpretable-through-prototypes deepfake detection for diffusion models
* Learning Interpretable Forensic Representations via Local Window Modulation
* Online Detection of AI-Generated Images
* Revisiting Generalizability in Deepfake Detection: Improving Metrics and Stabilizing Transfer
* TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization
* Undercover Deepfakes: Detecting Fake Segments in Videos
* WaterLo: Protect Images from Deepfakes Using Localized Semi-Fragile Watermark
13 for DFAD23
DFAD24
* *DeepFake Analysis and Detection
* Deepfake Catcher: Can a Simple Fusion be Effective and Outperform Complex DNNs?
* Demographic Bias Effects on Face Image Synthesis
* DiffSeg: Towards Detecting Diffusion-Based Inpainting Attacks Using Multi-Feature Segmentation
* Evaluating the Integration of Morph Attack Detection in Automated Face Recognition Systems
* Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks
* Latent Flow Diffusion for Deepfake Video Generation
* MaskSim: Detection of synthetic images by masked spectrum similarity analysis
* PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection
* Quality-based Artifact Modeling for Facial Deepfake Detection in Videos
* Temporal surface frame anomalies for deepfake video detection
11 for DFAD24