5 papers · 1 filter
What is Adversarial Training for Diffusion Models?
Briglia Maria Rosaria, Mujtaba Hussain Mirza, Giuseppe Lisanti +1
We answer the question in the title, showing that adversarial training (AT) for diffusion models (DMs) fundamentally differs from classifiers: while AT in classifiers enforces outp…
Language-guided Hierarchical Fine-grained Image Forgery Detection and Localization
Xiao Guo, Xiaohong Liu, Iacopo Masi +1
Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make a unified image forgery detection and locali…
Environment Maps Editing using Inverse Rendering and Adversarial Implicit Functions
Antonio D'Orazio, Davide Sforza, Fabio Pellacini +1
Editing High Dynamic Range (HDR) environment maps using an inverse differentiable rendering architecture is a complex inverse problem due to the sparsity of relevant pixels and the…
Perturb, Attend, Detect and Localize (PADL): Robust Proactive Image Defense
Filippo Bartolucci, Iacopo Masi, Giuseppe Lisanti
Image manipulation detection and localization have received considerable attention from the research community given the blooming of Generative Models (GMs). Detection methods that…
Shedding More Light on Robust Classifiers under the lens of Energy-based Models
Mujtaba Hussain Mirza, Maria Rosaria Briglia, Senad Beadini +1
By reinterpreting a robust discriminative classifier as Energy-based Model (EBM), we offer a new take on the dynamics of adversarial training (AT). Our analysis of the energy lands…