Review of automatic processing of topography and surface feature identification LiDAR data using machine learning techniques
Machine Learning (ML) applications on Light Detection And Ranging (LiDAR) data have
provided promising results and thus this topic has been widely addressed in the literature …
provided promising results and thus this topic has been widely addressed in the literature …
Improving visual grounding with visual-linguistic verification and iterative reasoning
Visual grounding is a task to locate the target indicated by a natural language expression.
Existing methods extend the generic object detection framework to this problem. They base …
Existing methods extend the generic object detection framework to this problem. They base …
Translo: A window-based masked point transformer framework for large-scale lidar odometry
Recently, transformer architecture has gained great success in the computer vision
community, such as image classification, object detection, etc. Nonetheless, its application …
community, such as image classification, object detection, etc. Nonetheless, its application …
Rnnpose: Recurrent 6-dof object pose refinement with robust correspondence field estimation and pose optimization
DoF object pose estimation from a monocular image is challenging, and a post-refinement
procedure is generally needed for high-precision estimation. In this paper, we propose a …
procedure is generally needed for high-precision estimation. In this paper, we propose a …
4drvo-net: Deep 4d radar–visual odometry using multi-modal and multi-scale adaptive fusion
Four-dimensional (4D) radar–visual odometry (4DRVO) integrates complementary
information from 4D radar and cameras, making it an attractive solution for achieving …
information from 4D radar and cameras, making it an attractive solution for achieving …
Efficient deep-learning 4d automotive radar odometry method
Odometry is a crucial technology for the autonomous positioning of intelligent vehicles.
While estimating the odometry from LiDAR and cameras has progressed recently, it remains …
While estimating the odometry from LiDAR and cameras has progressed recently, it remains …
Rnnpose: 6-dof object pose estimation via recurrent correspondence field estimation and pose optimization
6-DoF object pose estimation from a monocular image is a challenging problem, where a
post-refinement procedure is generally needed for high-precision estimation. In this paper …
post-refinement procedure is generally needed for high-precision estimation. In this paper …
Multi-view 3D data fusion and patching to reduce Shannon entropy in Robotic Vision
Abstract Optical Sensors Fusion is intended to enrich the data obtained from Robotic Vision
systems, which play a crucial role in applications such as machine guidance and monitoring …
systems, which play a crucial role in applications such as machine guidance and monitoring …
Hpplo-net: Unsupervised lidar odometry using a hierarchical point-to-plane solver
High-precision LiDAR odometry (LO) plays an essential role in autonomous driving.
Generally, due to inaccurate data associations and the existence of outliers, it is a …
Generally, due to inaccurate data associations and the existence of outliers, it is a …
Simulation-Based Self-Supervised Line Extraction for LiDAR Odometry in Urban Road Scenes
P Wang, R Zhou, C Dai, H Wang, W Jiang, Y Zhang - Remote Sensing, 2023 - mdpi.com
LiDAR odometry is a fundamental task for high-precision map construction and real-time
and accurate localization in autonomous driving. However, point clouds in urban road …
and accurate localization in autonomous driving. However, point clouds in urban road …