2 citations · 5 across the 10 of their papers we have counts for
9 papers · 1 filter
Representation and Reference Selection in Training-Free Synthetic Image Attribution
Meiling Li, Pietro Bongini, Benedetta Tondi +1
Synthetic image attribution aims at identifying the generator responsible for a given AI-generated image. Training-free reference-based attribution methods are easily scalable, sin…
Enhancing Visual Sentiment Analysis via Semiotic Isotopy-Guided Dataset Construction
Marco Blanchini, Giovanna Maria Dimitri, Benedetta Tondi +2
Visual Sentiment Analysis (VSA) is a challenging task due to the vast diversity of emotionally salient images and the inherent difficulty of acquiring sufficient data to capture th…
Training-free Source Attribution of AI-generated Images via Resynthesis
Pietro Bongini, Valentina Molinari, Andrea Costanzo +2
Synthetic image source attribution is a challenging task, especially in data scarcity conditions requiring few-shot or zero-shot classification capabilities. We present a new train…
An Efficient Watermarking Method for Latent Diffusion Models via Low-Rank Adaptation and Dynamic Loss Weighting
Dongdong Lin, Yue Li, Benedetta Tondi +3
The rapid proliferation of Deep Neural Networks (DNNs) is driving a surge in model watermarking technologies, as the trained models themselves constitute valuable intellectual prop…
Deepfake Media Forensics: State of the Art and Challenges Ahead
Irene Amerini, Mauro Barni, Sebastiano Battiato +21
AI-generated synthetic media, also called Deepfakes, have significantly influenced so many domains, from entertainment to cybersecurity. Generative Adversarial Networks (GANs) and…
BOSC: A Backdoor-based Framework for Open Set Synthetic Image Attribution
Jun Wang, Benedetta Tondi, Mauro Barni
Synthetic image attribution addresses the problem of tracing back the origin of images produced by generative models. Extensive efforts have been made to explore unique representat…