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cs.CV2026

SAR Vessel Detection and Gross Tonnage Estimation from Heterogeneous Datasets for Dark Vessel Identification

Davide Paltrinieri, Andrea Diecidue, Roberto Basla +3

Detecting vessels engaging in illegal activities is of paramount importance for maritime security. One of the major goals is to detect dark vessels, ships that disable their transp…

cs.CV2026

Cell Phantom Video Generation in Elliptical Fourier Descriptor Domain

Francesco Benedetto, Roberto Basla, Luca Magri +1

Training Deep Neural Networks for tracking individual cells in biomedical videos requires a large amount of annotated data. The annotation of videos for cell tracking is very time…

cs.CV20264 cited

LCF3D: A Robust and Real-Time Late-Cascade Fusion Framework for 3D Object Detection in Autonomous Driving

Carlo Sgaravatti, Riccardo Pieroni, Matteo Corno +3

Accurately localizing 3D objects like pedestrians, cyclists, and other vehicles is essential in Autonomous Driving. To ensure high detection performance, Autonomous Vehicles comple…

cs.CV2026

Promptable Foundation Models for SAR Remote Sensing: Adapting the Segment Anything Model for Snow Avalanche Segmentation

Riccardo Gelato, Carlo Sgaravatti, Jakob Grahn +2

Remote sensing solutions for avalanche segmentation and mapping are key to supporting risk forecasting and mitigation in mountain regions. Synthetic Aperture Radar (SAR) imagery fr…

cs.CV2025

One target to align them all: LiDAR, RGB and event cameras extrinsic calibration for Autonomous Driving

Andrea Bertogalli, Giacomo Boracchi, Luca Magri

We present a novel multi-modal extrinsic calibration framework designed to simultaneously estimate the relative poses between event cameras, LiDARs, and RGB cameras, with particula…

cs.CV2025

Convolutional Set Transformer

Federico Chinello, Giacomo Boracchi

We introduce the Convolutional Set Transformer (CST), a novel neural architecture designed to process image sets of arbitrary cardinality that are visually heterogeneous yet share…