Zobrazeno 1 - 10
of 768
pro vyhledávání: '"Marcotegui, A."'
Publikováno v:
In Fisheries Research November 2024 279
Paris-CARLA-3D: A Real and Synthetic Outdoor Point Cloud Dataset for Challenging Tasks in 3D Mapping
Autor:
Deschaud, Jean-Emmanuel, Duque, David, Richa, Jean Pierre, Velasco-Forero, Santiago, Marcotegui, Beatriz, Goulette, and François
Paris-CARLA-3D is a dataset of several dense colored point clouds of outdoor environments built by a mobile LiDAR and camera system. The data are composed of two sets with synthetic data from the open source CARLA simulator (700 million points) and r
Externí odkaz:
http://arxiv.org/abs/2111.11348
Autor:
Gigli, Leonardo, Kiran, B Ravi, Paul, Thomas, Serna, Andres, Vemuri, Nagarjuna, Marcotegui, Beatriz, Velasco-Forero, Santiago
Point cloud datasets for perception tasks in the context of autonomous driving often rely on high resolution 64-layer Light Detection and Ranging (LIDAR) scanners. They are expensive to deploy on real-world autonomous driving sensor architectures whi
Externí odkaz:
http://arxiv.org/abs/2005.13102
Akademický článek
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Akademický článek
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Autor:
Thomas, Hugues, Qi, Charles R., Deschaud, Jean-Emmanuel, Marcotegui, Beatriz, Goulette, François, Guibas, Leonidas J.
We present Kernel Point Convolution (KPConv), a new design of point convolution, i.e. that operates on point clouds without any intermediate representation. The convolution weights of KPConv are located in Euclidean space by kernel points, and applie
Externí odkaz:
http://arxiv.org/abs/1904.08889
Autor:
Peris, Irene, Romero-Murillo, Silvia, Martínez-Balsalobre, Elena, Farrington, Caroline C., Arriazu, Elena, Marcotegui, Nerea, Jiménez-Muñoz, Marta, Alburquerque-Prieto, Cristina, Torres-López, Andrea, Fresquet, Vicente, Martínez-Climent, Jose A., Mateos, Maria C., Cayuela, Maria L., Narla, Goutham, Odero, Maria D. ∗∗, ∗, Vicente, Carmen ∗, ∗
Publikováno v:
In Blood 2 March 2023 141(9):1047-1059
Autor:
Thomas, Hugues, Deschaud, Jean-Emmanuel, Marcotegui, Beatriz, Goulette, François, Gall, Yann Le
This paper introduces a new definition of multiscale neighborhoods in 3D point clouds. This definition, based on spherical neighborhoods and proportional subsampling, allows the computation of features with a consistent geometrical meaning, which is
Externí odkaz:
http://arxiv.org/abs/1808.00495
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2022, Pp 185-192 (2022)
LiDAR (Light Detection And Ranging) laser scanners acquire 3D point clouds of real environments. The process consists in sampling the scene with laser beams rotating around an axis. By construction, the point density decreases with the distance to th
Externí odkaz:
https://doaj.org/article/a87b98970f7747a4aa49a826dfffdf8f
Autor:
Lanfranchi, Ana L., Canel, Delfina, Alarcos, Ana J., Levy, Eugenia, Braicovich, Paola E., Marcotegui, Paula, Timi, Juan T.
Publikováno v:
Reviews in Fish Biology & Fisheries; Sep2024, Vol. 34 Issue 3, p1149-1166, 18p