Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Planamente, Mirco"'
Autor:
Peirone, Simone Alberto, Goletto, Gabriele, Planamente, Mirco, Bottino, Andrea, Caputo, Barbara, Averta, Giuseppe
Human activities exhibit a strong correlation between actions and the places where these are performed, such as washing something at a sink. More specifically, in daily living environments we may identify particular locations, hereinafter named activ
Externí odkaz:
http://arxiv.org/abs/2409.14205
To enable a safe and effective human-robot cooperation, it is crucial to develop models for the identification of human activities. Egocentric vision seems to be a viable solution to solve this problem, and therefore many works provide deep learning
Externí odkaz:
http://arxiv.org/abs/2211.03004
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition. To tackle the domain-shift which exists under the UDA setting, we first exploited a rec
Externí odkaz:
http://arxiv.org/abs/2209.04525
Autor:
Plizzari, Chiara, Planamente, Mirco, Goletto, Gabriele, Cannici, Marco, Gusso, Emanuele, Matteucci, Matteo, Caputo, Barbara
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". Due to their sensing mechanism, event cameras have little to no motion blur, a very high temporal resolution and require
Externí odkaz:
http://arxiv.org/abs/2112.03596
First person action recognition is becoming an increasingly researched area thanks to the rising popularity of wearable cameras. This is bringing to light cross-domain issues that are yet to be addressed in this context. Indeed, the information extra
Externí odkaz:
http://arxiv.org/abs/2110.10101
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition. To tackle the domain-shift which exists under the UDA setting, we first exploited a rec
Externí odkaz:
http://arxiv.org/abs/2107.00337
First person action recognition is an increasingly researched topic because of the growing popularity of wearable cameras. This is bringing to light cross-domain issues that are yet to be addressed in this context. Indeed, the information extracted f
Externí odkaz:
http://arxiv.org/abs/2106.01689
Autor:
Planamente, Mirco, Plizzari, Chiara, Cannici, Marco, Ciccone, Marco, Strada, Francesco, Bottino, Andrea, Matteucci, Matteo, Caputo, Barbara
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". The innovative way they acquire data presents several advantages over standard devices, especially in poor lighting and
Externí odkaz:
http://arxiv.org/abs/2103.12768
Autor:
Loghmani, Mohammad Reza, Robbiano, Luca, Planamente, Mirco, Park, Kiru, Caputo, Barbara, Vincze, Markus
Unsupervised Domain Adaptation (DA) exploits the supervision of a label-rich source dataset to make predictions on an unlabeled target dataset by aligning the two data distributions. In robotics, DA is used to take advantage of automatically generate
Externí odkaz:
http://arxiv.org/abs/2004.10016
Wearable cameras are becoming more and more popular in several applications, increasing the interest of the research community in developing approaches for recognizing actions from the first-person point of view. An open challenge in egocentric actio
Externí odkaz:
http://arxiv.org/abs/2002.03982