8 papers
Code Division Modulation Layers Against Forgetting and Inference in Continual Gait Identification
Simone Milani
Continual learning (CL) has been recently employed in biometric identification systems thanks to its ability to integrate new knowledge within a pre-trained model and to the possib…
Traceback Translators Against Forgetting in Continual Fake Speech Detection
Enrico Gottardis, Mattia Tamiazzo, Simone Milani
Fake speech detectors are increasingly challenged by the development of new and more accurate generative models. To cope with this problem, continual learning techniques are nowada…
TeLL Me what you cant see
Saverio Cavasin, Pietro Biasetton, Mattia Tamiazzo +2
During criminal investigations, images of persons of interest directly influence the success of identification procedures. However, law enforcement agencies often face challenges r…
Point Cloud Geometry Scalable Coding Using a Resolution and Quality-conditioned Latents Probability Estimator
Daniele Mari, André F. R. Guarda, Nuno M. M. Rodrigues +2
In the current age, users consume multimedia content in very heterogeneous scenarios in terms of network, hardware, and display capabilities. A naive solution to this problem is to…
Effectiveness of learning-based image codecs on fingerprint storage
Daniele Mari, Saverio Cavasin, Simone Milani +1
The success of learning-based coding techniques and the development of learning-based image coding standards, such as JPEG-AI, point towards the adoption of such solutions in diffe…
Fingerprint Membership and Identity Inference Against Generative Adversarial Networks
Saverio Cavasin, Daniele Mari, Simone Milani +1
Generative models are gaining significant attention as potential catalysts for a novel industrial revolution. Since automated sample generation can be useful to solve privacy and d…
Point Cloud Geometry Scalable Coding with a Quality-Conditioned Latents Probability Estimator
Daniele Mari, André F. R. Guarda, Nuno M. M. Rodrigues +2
The widespread usage of point clouds (PC) for immersive visual applications has resulted in the use of very heterogeneous receiving conditions and devices, notably in terms of netw…
Enhancing the Rate-Distortion-Perception Flexibility of Learned Image Codecs with Conditional Diffusion Decoders
Daniele Mari, Simone Milani
Learned image compression codecs have recently achieved impressive compression performances surpassing the most efficient image coding architectures. However, most approaches are t…