Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Palazzi, Andrea"'
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 fashion is still far from being achieved. Instead, here we follow a two
Externí odkaz:
http://arxiv.org/abs/2007.00323
In this work we introduce a new self-supervised, semi-parametric approach for synthesizing novel views of a vehicle starting from a single monocular image. Differently from parametric (i.e. entirely learning-based) methods, we show how a-priori geome
Externí odkaz:
http://arxiv.org/abs/1907.10634
Autor:
Fabbri, Matteo, Lanzi, Fabio, Calderara, Simone, Palazzi, Andrea, Vezzani, Roberto, Cucchiara, Rita
Multi-People Tracking in an open-world setting requires a special effort in precise detection. Moreover, temporal continuity in the detection phase gains more importance when scene cluttering introduces the challenging problems of occluded targets. F
Externí odkaz:
http://arxiv.org/abs/1803.08319
Awareness of the road scene is an essential component for both autonomous vehicles and Advances Driver Assistance Systems and is gaining importance both for the academia and car companies. This paper presents a way to learn a semantic-aware transform
Externí odkaz:
http://arxiv.org/abs/1706.08442
In this work we aim to predict the driver's focus of attention. The goal is to estimate what a person would pay attention to while driving, and which part of the scene around the vehicle is more critical for the task. To this end we propose a new com
Externí odkaz:
http://arxiv.org/abs/1705.03854
Despite the advent of autonomous cars, it's likely - at least in the near future - that human attention will still maintain a central role as a guarantee in terms of legal responsibility during the driving task. In this paper we study the dynamics of
Externí odkaz:
http://arxiv.org/abs/1611.08215
Autor:
Solera, Francesco, Palazzi, Andrea
We provide a distribution-free test that can be used to determine whether any two joint distributions $p$ and $q$ are statistically different by inspection of a large enough set of samples. Following recent efforts from Long et al. [1], we rely on jo
Externí odkaz:
http://arxiv.org/abs/1607.07270
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.