From the 1 of 9 linked papers with an AI index.
9 papers
Representation and Reference Selection in Training-Free Synthetic Image Attribution
Meiling Li, Pietro Bongini, Benedetta Tondi +1
The paper investigates how the choice of visual representation and reference selection method affect training‑free, reference‑based attribution of synthetic images, showing that in…
The Role of Input Dimensionality in the Emergence and Targeted Control of Adversarial Examples
Nasrin Malekzadeh Goradel, Niccolo Pancino, Yaser Gholizade Atani +3
Several theoretical works have tried to explain the adversarial vulnerability of deep neural networks through properties of high-dimensional geometry. However, the assumptions unde…
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…
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…
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…
Of-SemWat: High-payload text embedding for semantic watermarking of AI-generated images with arbitrary size
Benedetta Tondi, Andrea Costanzo, Mauro Barni
We propose a high-payload image watermarking method for textual embedding, where a semantic description of the image - which may also correspond to the input text prompt-, is embed…