3 papers
cs.LG2025
Federated Class-Incremental Learning with Hierarchical Generative Prototypes
Riccardo Salami, Pietro Buzzega, Matteo Mosconi +2
Federated Learning (FL) aims at unburdening the training of deep models by distributing computation across multiple devices (clients) while safeguarding data privacy. On top of tha…
cs.CV2025
Monocular Per-Object Distance Estimation with Masked Object Modeling
Aniello Panariello, Gianluca Mancusi, Fedy Haj Ali +3
Per-object distance estimation is critical in surveillance and autonomous driving, where safety is crucial. While existing methods rely on geometric or deep supervised features, on…
cs.CV2024
Is Multiple Object Tracking a Matter of Specialization?
Gianluca Mancusi, Mattia Bernardi, Aniello Panariello +3
End-to-end transformer-based trackers have achieved remarkable performance on most human-related datasets. However, training these trackers in heterogeneous scenarios poses signifi…