1 code implementation • 25 Apr 2022 • Luigi Filippo Chiara, Pasquale Coscia, Sourav Das, Simone Calderara, Rita Cucchiara, Lamberto Ballan
Human trajectory forecasting is a key component of autonomous vehicles, social-aware robots and advanced video-surveillance applications.
no code implementations • CVPR 2022 • Alessio Monti, Angelo Porrello, Simone Calderara, Pasquale Coscia, Lamberto Ballan, Rita Cucchiara
To this end, we conceive a novel distillation strategy that allows a knowledge transfer from a teacher network to a student one, the latter fed with fewer observations (just two ones).
no code implementations • 2 Sep 2021 • Nada Osman, Guglielmo Camporese, Pasquale Coscia, Lamberto Ballan
Action anticipation in egocentric videos is a difficult task due to the inherently multi-modal nature of human actions.
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 • 16 Apr 2020 • Guglielmo Camporese, Pasquale Coscia, Antonino Furnari, Giovanni Maria Farinella, Lamberto Ballan
Since multiple actions may equally occur in the future, we treat action anticipation as a multi-label problem with missing labels extending the concept of label smoothing.
no code implementations • 13 Oct 2019 • Tobia Tesan, Pasquale Coscia, Lamberto Ballan
Images represent a commonly used form of visual communication among people.
1 code implementation • 19 Sep 2019 • Matteo Lisotto, Pasquale Coscia, Lamberto Ballan
Mimicking human ability to forecast future positions or interpret complex interactions in urban scenarios, such as streets, shopping malls or squares, is essential to develop socially compliant robots or self-driving cars.
no code implementations • 7 Apr 2016 • Pasquale Coscia, Francesco A. N. Palmieri, Francesco Castaldo, Alberto Cavallo
We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor.