Self-Supervised Depth Completion From Direct Visual-LiDAR Odometry in Autonomous Driving
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3106055
Abstract: In this work, a simple yet effective deep neural network is proposed to generate the dense depth map of the scene by exploiting both LiDAR sparse point cloud and the monocular camera image. Specifically, a… read more here.
Keywords: network; completion; lidar odometry; depth completion ... See more keywords
Efficient and Accurate Tightly-Coupled Visual-Lidar SLAM
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3130089
Abstract: We investigate a novel way to integrate visual SLAM and lidar SLAM. Instead of enhancing visual odometry via lidar depths or using visual odometry as the motion initial guess of lidar odometry, we propose tightly-coupled… read more here.
Keywords: coupled visual; tightly coupled; lidar slam; lidar ... See more keywords
SDV-LOAM: Semi-Direct Visual-LiDAR Odometry and Mapping.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3262817
Abstract: Visual-LiDAR odometry and mapping (V-LOAM), which fuses complementary information of a camera and a LiDAR, is an attractive solution for accurate and robust pose estimation and mapping. However, existing systems could suffer nontrivial tracking errors… read more here.
Keywords: sdv loam; odometry; lidar odometry; lidar ... See more keywords