36 citations · 48 across the 9 of their papers we have counts for
5 papers · 1 filter
Learning to Generalize One Sample at a Time with Self-Supervision
Antonio D'Innocente, Silvia Bucci, Barbara Caputo +1
Although deep networks have significantly increased the performance of visual recognition methods, it is still challenging to achieve the robustness across visual domains that is n…
Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition
Massimiliano Mancini, Hakan Karaoguz, Elisa Ricci +2
While today's robots are able to perform sophisticated tasks, they can only act on objects they have been trained to recognize. This is a severe limitation: any robot will inevitab…
Domain Generalization by Solving Jigsaw Puzzles
Fabio Maria Carlucci, Antonio D'Innocente, Silvia Bucci +2
Human adaptability relies crucially on the ability to learn and merge knowledge both from supervised and unsupervised learning: the parents point out few important concepts, but th…
The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots
Fabio Cermelli, Massimiliano Mancini, Elisa Ricci +1
Deep networks have brought significant advances in robot perception, enabling to improve the capabilities of robots in several visual tasks, ranging from object detection and recog…
AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo +1
The ability to categorize is a cornerstone of visual intelligence, and a key functionality for artificial, autonomous visual machines. This problem will never be solved without alg…