activity
20242026
collaborators

8 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

Chroma Clues: Leveraging Color Statistics to Detect Synthetic Images

Lea Uhlenbrock, Davide Cozzolino, Christian Riess

The evolution and dissemination of AI-synthesized images is occurring at an unprecedented rate. Image generators are making rapid progress in their goal of perfectly imitating natu…

cs.CV2026

Quality-Aware Calibration for AI-Generated Image Detection in the Wild

Fabrizio Guillaro, Vincenzo De Rosa, Davide Cozzolino +1

Significant progress has been made in detecting synthetic images, however most existing approaches operate on a single image instance and overlook a key characteristic of real-worl…

cs.CV2025

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…

cs.CV2025

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…