Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Berra, Riccardo"'
Autor:
Taioli, Francesco, Giuliari, Francesco, Wang, Yiming, Berra, Riccardo, Castellini, Alberto, Del Bue, Alessio, Farinelli, Alessandro, Cristani, Marco, Setti, Francesco
We propose a solution for Active Visual Search of objects in an environment, whose 2D floor map is the only known information. Our solution has three key features that make it more plausible and robust to detector failures compared to state-of-the-ar
Externí odkaz:
http://arxiv.org/abs/2303.03155
Autor:
Giuliari, Francesco, Castellini, Alberto, Berra, Riccardo, Del Bue, Alessio, Farinelli, Alessandro, Cristani, Marco, Setti, Francesco, Wang, Yiming
In this paper we focus on the problem of learning online an optimal policy for Active Visual Search (AVS) of objects in unknown indoor environments. We propose POMP++, a planning strategy that introduces a novel formulation on top of the classic Part
Externí odkaz:
http://arxiv.org/abs/2107.00914
Autor:
Wang, Yiming, Giuliari, Francesco, Berra, Riccardo, Castellini, Alberto, Del Bue, Alessio, Farinelli, Alessandro, Cristani, Marco, Setti, Francesco
In this paper we focus on the problem of learning an optimal policy for Active Visual Search (AVS) of objects in known indoor environments with an online setup. Our POMP method uses as input the current pose of an agent (e.g. a robot) and a RGB-D fra
Externí odkaz:
http://arxiv.org/abs/2009.08140
Autor:
Taioli, Francesco, Giuliari, Francesco, Wang, Yiming, Berra, Riccardo, Castellini, Alberto, Bue, Alessio Del, Farinelli, Alessandro, Cristani, Marco, Setti, Francesco
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence; December 2024, Vol. 46 Issue: 12 p11047-11058, 12p
Autor:
Yiming Wang, Giuliari, Francesco, Berra, Riccardo, Castellini, Alberto, Bue, Del Alessio, Farinelli, Alessandro, Cristani, Marco, Setti, Francesco
Publikováno v:
Università degli Studi di Verona-IRIS
Fondazione Bruno Kessler-IRIS
Fondazione Bruno Kessler-IRIS
In this paper we focus on the problem of learning an optimal policy for Active Visual Search (AVS) of objects in known indoor environments with an online setup. Our POMP method uses as input the current pose of an agent (e.g. a robot) and a RGB-D fra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7daed1b8d703418dbb09e78aeb3445c9
https://iris.univr.it/handle/11562/1035533
https://iris.univr.it/handle/11562/1035533