Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Ciampi, Luca"'
Autor:
Ciampi, Luca, Messina, Nicola, Pierucci, Matteo, Amato, Giuseppe, Avvenuti, Marco, Falchi, Fabrizio
Class-agnostic counting (CAC) is a recent task in computer vision that aims to estimate the number of instances of arbitrary object classes never seen during model training. With the recent advancement of robust vision-and-language foundation models,
Externí odkaz:
http://arxiv.org/abs/2409.15953
Autor:
Foszner, Paweł, Szczęsna, Agnieszka, Ciampi, Luca, Messina, Nicola, Cygan, Adam, Bizoń, Bartosz, Cogiel, Michał, Golba, Dominik, Macioszek, Elżbieta, Staniszewski, Michał
Publikováno v:
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2023
Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or other sensors). The use of simulation tools can significantly reduce the t
Externí odkaz:
http://arxiv.org/abs/2304.13403
Autor:
Foszner, Paweł, Szczęsna, Agnieszka, Ciampi, Luca, Messina, Nicola, Cygan, Adam, Bizoń, Bartosz, Cogiel, Michał, Golba, Dominik, Macioszek, Elżbieta, Staniszewski, Michał
Data scarcity has become one of the main obstacles to developing supervised models based on Artificial Intelligence in Computer Vision. Indeed, Deep Learning-based models systematically struggle when applied in new scenarios never seen during trainin
Externí odkaz:
http://arxiv.org/abs/2304.05090
Autor:
Avvenuti, Marco, Bongiovanni, Marco, Ciampi, Luca, Falchi, Fabrizio, Gennaro, Claudio, Messina, Nicola
Automatic people counting from images has recently drawn attention for urban monitoring in modern Smart Cities due to the ubiquity of surveillance camera networks. Current computer vision techniques rely on deep learning-based algorithms that estimat
Externí odkaz:
http://arxiv.org/abs/2208.11339
Autor:
Ciampi, Luca
In this dissertation, we investigated and enhanced Deep Learning (DL) techniques for counting objects, like pedestrians, cells or vehicles, in still images or video frames. In particular, we tackled the challenge related to the lack of data needed fo
Externí odkaz:
http://arxiv.org/abs/2206.03033
Autor:
Cafarelli, Donato, Ciampi, Luca, Vadicamo, Lucia, Gennaro, Claudio, Berton, Andrea, Paterni, Marco, Benvenuti, Chiara, Passera, Mirko, Falchi, Fabrizio
Modern Unmanned Aerial Vehicles (UAV) equipped with cameras can play an essential role in speeding up the identification and rescue of people who have fallen overboard, i.e., man overboard (MOB). To this end, Artificial Intelligence techniques can be
Externí odkaz:
http://arxiv.org/abs/2203.07973
Autor:
Ciampi, Luca, Gennaro, Claudio, Carrara, Fabio, Falchi, Fabrizio, Vairo, Claudio, Amato, Giuseppe
This paper presents a novel solution to automatically count vehicles in a parking lot using images captured by smart cameras. Unlike most of the literature on this task, which focuses on the analysis of single images, this paper proposes the use of m
Externí odkaz:
http://arxiv.org/abs/2106.02842
Monitoring vehicle flows in cities is crucial to improve the urban environment and quality of life of citizens. Images are the best sensing modality to perceive and assess the flow of vehicles in large areas. Current technologies for vehicle counting
Externí odkaz:
http://arxiv.org/abs/2004.09251
Publikováno v:
Sensors 20.18 (2020): 5250
Pedestrian detection through Computer Vision is a building block for a multitude of applications. Recently, there was an increasing interest in Convolutional Neural Network-based architectures for the execution of such a task. One of these supervised
Externí odkaz:
http://arxiv.org/abs/2001.03032
Autor:
Ciampi, Luca, Zeni, Valeria, Incrocci, Luca, Canale, Angelo, Benelli, Giovanni, Falchi, Fabrizio, Amato, Giuseppe, Chessa, Stefano
Publikováno v:
In Ecological Informatics December 2023 78
