3 accepted papers
The rapid advancement of generators (e.g., StyleGAN, Midjourney, DALL-E) has produced highly realistic synthetic images, posing significant challenges to digital media authenticity. These generators are typically based on a few core architectural families, primarily Generative Adversarial Networks (
Anomaly detection (AD) on real-world tabular data is challenged by scarce labels, diverse anomaly types, and high sensitivity to data-specific hyperparameter tuning. We propose Discriminant Vector Machine for Anomaly detection (DVM-AD), a robust one-class method derived from discriminant analysis wi…
Deepfake (DF) detectors face significant challenges when deployed in real-world environments, particularly when encountering test samples deviated from training data through either postprocessing manipulations or distribution shifts. We demonstrate postprocessing techniques can completely obscure ge