127 citations · 420 across the 42 of their papers we have counts for
11 papers · 1 filter
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…
Few-Shot Unsupervised Continual Learning through Meta-Examples
Alessia Bertugli, Stefano Vincenzi, Simone Calderara +1
In real-world applications, data do not reflect the ones commonly used for neural networks training, since they are usually few, unlabeled and can be available as a stream. Hence m…
Inter-Homines: Distance-Based Risk Estimation for Human Safety
Matteo Fabbri, Fabio Lanzi, Riccardo Gasparini +3
In this document, we report our proposal for modeling the risk of possible contagiousity in a given area monitored by RGB cameras where people freely move and interact. Our system,…
Robust Re-Identification by Multiple Views Knowledge Distillation
Angelo Porrello, Luca Bergamini, Simone Calderara
To achieve robustness in Re-Identification, standard methods leverage tracking information in a Video-To-Video fashion. However, these solutions face a large drop in performance fo…
Future Urban Scenes Generation Through Vehicles Synthesis
Alessandro Simoni, Luca Bergamini, Andrea Palazzi +2
In this work we propose a deep learning pipeline to predict the visual future appearance of an urban scene. Despite recent advances, generating the entire scene in an end-to-end fa…
The color out of space: learning self-supervised representations for Earth Observation imagery
Stefano Vincenzi, Angelo Porrello, Pietro Buzzega +6
The recent growth in the number of satellite images fosters the development of effective deep-learning techniques for Remote Sensing (RS). However, their full potential is untapped…
DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting
Alessio Monti, Alessia Bertugli, Simone Calderara +1
Understanding human motion behaviour is a critical task for several possible applications like self-driving cars or social robots, and in general for all those settings where an au…
AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction
Alessia Bertugli, Simone Calderara, Pasquale Coscia +2
Anticipating human motion in crowded scenarios is essential for developing intelligent transportation systems, social-aware robots and advanced video surveillance applications. A k…
Dark Experience for General Continual Learning: a Strong, Simple Baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello +2
Continual Learning has inspired a plethora of approaches and evaluation settings; however, the majority of them overlooks the properties of a practical scenario, where the data str…
Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation
Matteo Fabbri, Fabio Lanzi, Simone Calderara +2
In this paper we present a novel approach for bottom-up multi-person 3D human pose estimation from monocular RGB images. We propose to use high resolution volumetric heatmaps to mo…
Conditional Channel Gated Networks for Task-Aware Continual Learning
Davide Abati, Jakub Tomczak, Tijmen Blankevoort +3
Convolutional Neural Networks experience catastrophic forgetting when optimized on a sequence of learning problems: as they meet the objective of the current training examples, the…