Lasermix for semi-supervised lidar semantic segmentation
Densely annotating LiDAR point clouds is costly, which often restrains the scalability of fully-
supervised learning methods. In this work, we study the underexplored semi-supervised …
supervised learning methods. In this work, we study the underexplored semi-supervised …
Multi-modal data-efficient 3d scene understanding for autonomous driving
Efficient data utilization is crucial for advancing 3D scene understanding in autonomous
driving, where reliance on heavily human-annotated LiDAR point clouds challenges fully …
driving, where reliance on heavily human-annotated LiDAR point clouds challenges fully …
T-UDA: Temporal Unsupervised Domain Adaptation in Sequential Point Clouds
AH Gebrehiwot, D Hurych… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
Deep perception models have to reliably cope with an open-world setting of domain shifts
induced by different geographic regions, sensor properties, mounting positions, and several …
induced by different geographic regions, sensor properties, mounting positions, and several …
Učení 3D vnímání pomocí neanotovaných dat
V Patrik - 2024 - dspace.cvut.cz
Integrace technologiı́ 3D počı́tačového viděnı́, zejména bodových mraků LiDARu (Light
Detection and Ranging), zásadnı́m způsobem revolucionizovala oblasti jako je autonomnı́ …
Detection and Ranging), zásadnı́m způsobem revolucionizovala oblasti jako je autonomnı́ …