6 papers
Anchor-Regularized Adaptation for Generalizable AI-Generated Image Detection with DINOv3
Hyeongjun Choi, Juhun Lee, Davide Cozzolino +2
Recent works in AI-generated image detection have shown that careful training data alignment can improve generalization by removing spurious correlations. However, linear probes on…
Understanding Why Foundation Models Work for Diffusion-Generated Image Detection
Davide Cozzolino, Giovanni Poggi, Luisa Verdoliva
Vision foundation models have recently emerged as powerful feature extractors for detecting AI-generated images, achieving strong generalization across generators and robustness to…
AI-GenBench: A New Ongoing Benchmark for AI-Generated Image Detection
Lorenzo Pellegrini, Davide Cozzolino, Serafino Pandolfini +5
The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity…
Seeing What Matters: Generalizable AI-generated Video Detection with Forensic-Oriented Augmentation
Riccardo Corvi, Davide Cozzolino, Ekta Prashnani +3
Synthetic video generation is progressing very rapidly. The latest models can produce very realistic high-resolution videos that are virtually indistinguishable from real ones. Alt…
A Bias-Free Training Paradigm for More General AI-generated Image Detection
Fabrizio Guillaro, Giada Zingarini, Ben Usman +3
Successful forensic detectors can produce excellent results in supervised learning benchmarks but struggle to transfer to real-world applications. We believe this limitation is lar…
Exploring the Adversarial Robustness of CLIP for AI-generated Image Detection
Vincenzo De Rosa, Fabrizio Guillaro, Giovanni Poggi +2
In recent years, many forensic detectors have been proposed to detect AI-generated images and prevent their use for malicious purposes. Convolutional neural networks (CNNs) have lo…