1 code implementation • 28 Jan 2021 • Alessia Bertugli, Stefano Vincenzi, Simone Calderara, Andrea Passerini
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.
1 code implementation • 17 Sep 2020 • Alessia Bertugli, Stefano Vincenzi, Simone Calderara, Andrea Passerini
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.
1 code implementation • 26 May 2020 • Alessio Monti, Alessia Bertugli, Simone Calderara, Rita Cucchiara
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 autonomous agent has to navigate inside a human-centric environment.
Ranked #1 on Trajectory Prediction on STATS SportVu NBA [ATK]
Human motion prediction Multi-future Trajectory Prediction +3
1 code implementation • 17 May 2020 • Alessia Bertugli, Simone Calderara, Pasquale Coscia, Lamberto Ballan, Rita Cucchiara
Anticipating human motion in crowded scenarios is essential for developing intelligent transportation systems, social-aware robots and advanced video surveillance applications.
no code implementations • 8 Aug 2019 • Alessia Bertugli, Paolo Galeone
Unity 3D allowed us to simulate a real-world setup, where a depth camera is placed in a fixed position and the stream of images is used by our policy network to learn how to solve the task.