127 citations · 420 across the 42 of their papers we have counts for
5 papers · 1 filter
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Matteo Fabbri, Guillem Braso, Gianluca Maugeri +6
Deep learning-based methods for video pedestrian detection and tracking require large volumes of training data to achieve good performance. However, data acquisition in crowded pub…
Continual Semi-Supervised Learning through Contrastive Interpolation Consistency
Matteo Boschini, Pietro Buzzega, Lorenzo Bonicelli +2
Continual Learning (CL) investigates how to train Deep Networks on a stream of tasks without incurring forgetting. CL settings proposed in literature assume that every incoming exa…
Avalanche: an End-to-End Library for Continual Learning
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu +25
Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning. Recently, we have witnessed a renewed and fast-growing…
RMS-Net: Regression and Masking for Soccer Event Spotting
Matteo Tomei, Lorenzo Baraldi, Simone Calderara +2
The recently proposed action spotting task consists in finding the exact timestamp in which an event occurs. This task fits particularly well for soccer videos, where events corres…
Generalising via Meta-Examples for Continual Learning in the Wild
Alessia Bertugli, Stefano Vincenzi, Simone Calderara +1
Future deep learning systems call for techniques that can deal with the evolving nature of temporal data and scarcity of annotations when new problems occur. As a step towards this…