16 citations · 16 across the 4 of their papers we have counts for
5 papers
Multi-modal panoramic 3D outdoor datasets for place categorization
Hojung Jung, Yuki Oto, Oscar M. Mozos +2
We present two multi-modal panoramic 3D outdoor (MPO) datasets for semantic place categorization with six categories: forest, coast, residential area, urban area and indoor/outdoor…
Learning Geometric and Photometric Features from Panoramic LiDAR Scans for Outdoor Place Categorization
Kazuto Nakashima, Hojung Jung, Yuki Oto +3
Semantic place categorization, which is one of the essential tasks for autonomous robots and vehicles, allows them to have capabilities of self-decision and navigation in unfamilia…
Isomorphic mesh generation from point clouds with multilayer perceptrons
Shoko Miyauchi, Ken'ichi Morooka, Ryo Kurazume
We propose a new neural network, called isomorphic mesh generator (iMG), which generates isomorphic meshes from point clouds containing noise and missing parts. Isomorphic meshes o…
Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data
Kazuto Nakashima, Yumi Iwashita, Ryo Kurazume
3D LiDAR sensors are indispensable for the robust vision of autonomous mobile robots. However, deploying LiDAR-based perception algorithms often fails due to a domain gap from the…
Learning to Drop Points for LiDAR Scan Synthesis
Kazuto Nakashima, Ryo Kurazume
3D laser scanning by LiDAR sensors plays an important role for mobile robots to understand their surroundings. Nevertheless, not all systems have high resolution and accuracy due t…