Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Matteo, Poggi"'
Given sparse depths and the corresponding RGB images, depth completion aims at spatially propagating the sparse measurements throughout the whole image to get a dense depth prediction. Despite the tremendous progress of deep-learning-based depth comp
Externí odkaz:
http://arxiv.org/abs/2304.13030
Autor:
Daniele De Gregorio, Matteo Poggi, Pierluigi Zama Ramirez, Gianluca Palli, Stefano Mattoccia, Luigi Di Stefano
Publikováno v:
IEEE Access, Vol 9, Pp 119755-119765 (2021)
Self-aware robots rely on depth sensing to interact with the surrounding environment, e.g. to pursue object grasping. Yet, dealing with tiny items, often occurring in industrial robotics scenarios, may represent a challenge due to lack of sensors yie
Externí odkaz:
https://doaj.org/article/ca511c346b7f4aaab7ee7db6014415a6
Publikováno v:
Journal of High Energy Physics, Vol 2019, Iss 7, Pp 1-42 (2019)
Abstract We compute the elliptic genus of the D1/D7 brane system in flat space, finding a non-trivial dependence on the number of D7 branes, and provide an F-theory interpretation of the result. We show that the JK-residues contributing to the ellipt
Externí odkaz:
https://doaj.org/article/57a64cb3ac4449df9b8fd91771b4da8e
Autor:
Matteo Poggi
Publikováno v:
Journal of High Energy Physics, Vol 2018, Iss 3, Pp 1-16 (2018)
Abstract We study elliptic vortices on ℂ × T 2 by considering the 2d quiver gauge theory describing their moduli spaces. The elliptic genus of these moduli spaces is the elliptic version of vortex partition function of the 4d theory. We focus on t
Externí odkaz:
https://doaj.org/article/b348fbd321d54affb5d7d3dd1bb7be60
Autor:
Arsal-Hanif Livoroi, Andrea Conti, Luca Foianesi, Fabio Tosi, Filippo Aleotti, Matteo Poggi, Flavia Tauro, Elena Toth, Salvatore Grimaldi, Stefano Mattoccia
Publikováno v:
Applied Sciences, Vol 11, Iss 15, p 7027 (2021)
As reported in the recent image velocimetry literature, tracking the motion of sparse feature points floating on the river surface as done by the Optical Tracking Velocimetry (OTV) algorithm is a promising strategy to address surface flow monitoring.
Externí odkaz:
https://doaj.org/article/5dd54fb8019c41b8aefdb3e811744caf
Autor:
Matteo Poggi, Thomas B. Moeslund
Publikováno v:
Sensors, Vol 21, Iss 12, p 3944 (2021)
Effective 3D perception of an observed scene greatly enriches the knowledge about the surrounding environment and is crucial to effectively develop high-level applications for various purposes [...]
Externí odkaz:
https://doaj.org/article/bc92c8ae3ce0428cb8a1247025355bb2
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-17
Under-display imaging has recently received considerable attention in both academia and industry. As a variation of this technique, under-display ToF (UD-ToF) cameras enable depth sensing for full-screen devices. However, it also brings problems of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6eb8106d7153e8bee728dd244410f23e
https://doi.org/10.1109/tpami.2022.3209905
https://doi.org/10.1109/tpami.2022.3209905
Autor:
Valentino Peluso, Fabio Tosi, Stefano Mattoccia, Antonio Cipolletta, Andrea Calimera, Filippo Aleotti, Matteo Poggi
Publikováno v:
IEEE Internet of Things Journal. 9:25-36
The recent advancements in deep learning have demonstrated that inferring high-quality depth maps from a single image has become feasible and accurate, thanks to convolutional neural networks (CNNs), but how to process such compute- and memory-intens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98ae051e5ec3633e3fcda51d4c7d8716
https://doi.org/10.1109/jiot.2021.3080827
https://doi.org/10.1109/jiot.2021.3080827
Autor:
Jaime Spencer, C. Stella Qian, Chris Russell, Simon Hadfield, Erich Graf, Wendy Adams, Andrew J. Schofield, James Elder, Richard Bowden, Heng Cong, Stefano Mattoccia, Matteo Poggi, Zeeshan Khan Suri, Yang Tang, Fabio Tosi, Hao Wang, Youmin Zhang, Yusheng Zhang, Chaoqiang Zhao
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW).
This paper summarizes the results of the first Monocular Depth Estimation Challenge (MDEC) organized at WACV2023. This challenge evaluated the progress of self-supervised monocular depth estimation on the challenging SYNS-Patches dataset. The challen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9948cd528bbc04b8047ace8e541f0fff
https://doi.org/10.1109/wacvw58289.2023.00069
https://doi.org/10.1109/wacvw58289.2023.00069
Autor:
Filippo Aleotti, Giulio Zaccaroni, Luca Bartolomei, Matteo Poggi, Fabio Tosi, Stefano Mattoccia
Publikováno v:
Sensors, Vol 21, Iss 1, p 15 (2020)
Depth perception is paramount for tackling real-world problems, ranging from autonomous driving to consumer applications. For the latter, depth estimation from a single image would represent the most versatile solution since a standard camera is avai
Externí odkaz:
https://doaj.org/article/83e5aac131de4abd8bf18ee9b2d826a8