6 citations · 19 across the 13 of their papers we have counts for
27 papers
Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction
Luigi Filippo Chiara, Pasquale Coscia, Sourav Das +3
Human trajectory forecasting is a key component of autonomous vehicles, social-aware robots and advanced video-surveillance applications. This challenging task typically requires k…
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting
Alessio Monti, Angelo Porrello, Simone Calderara +3
Accurate prediction of future human positions is an essential task for modern video-surveillance systems. Current state-of-the-art models usually rely on a "history" of past tracke…
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…
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…
Rethinking Experience Replay: a Bag of Tricks for Continual Learning
Pietro Buzzega, Matteo Boschini, Angelo Porrello +1
In Continual Learning, a Neural Network is trained on a stream of data whose distribution shifts over time. Under these assumptions, it is especially challenging to improve on clas…