Learning object bounding boxes for 3d instance segmentation on point clouds
We propose a novel, conceptually simple and general framework for instance segmentation
on 3D point clouds. Our method, called 3D-BoNet, follows the simple design philosophy of …
on 3D point clouds. Our method, called 3D-BoNet, follows the simple design philosophy of …
Systematic and comprehensive review of clustering and multi-target tracking techniques for LiDAR point clouds in autonomous driving applications
Autonomous vehicles (AVs) rely on advanced sensory systems, such as Light Detection and
Ranging (LiDAR), to function seamlessly in intricate and dynamic environments. LiDAR …
Ranging (LiDAR), to function seamlessly in intricate and dynamic environments. LiDAR …
Fusemodnet: Real-time camera and lidar based moving object detection for robust low-light autonomous driving
Moving object detection is a critical task for autonomous vehicles. As dynamic objects
represent higher collision risk than static ones, our own ego-trajectories have to be planned …
represent higher collision risk than static ones, our own ego-trajectories have to be planned …
Cmrnet: Camera to lidar-map registration
In this paper we present CMRNet, a realtime approach based on a Convolutional Neural
Network (CNN) to localize an RGB image of a scene in a map built from LiDAR data. Our …
Network (CNN) to localize an RGB image of a scene in a map built from LiDAR data. Our …
Circular convolutional neural networks for panoramic images and laser data
S Schubert, P Neubert, J Pöschmann… - 2019 IEEE intelligent …, 2019 - ieeexplore.ieee.org
Circular Convolutional Neural Networks (CCNN) are an easy to use alternative to CNNs for
input data with wrap-around structure like 360° images and multi-layer laserscans. Although …
input data with wrap-around structure like 360° images and multi-layer laserscans. Although …
Deep generative modeling of lidar data
Building models capable of generating structured output is a key challenge for AI and
robotics. While generative models have been explored on many types of data, little work has …
robotics. While generative models have been explored on many types of data, little work has …
A robust pose graph approach for city scale LiDAR mapping
This paper presents a method for reconstructing globally consistent 3D High-Definition (HD)
maps at city scale. Current approaches for eliminating cumulative drift are mainly based on …
maps at city scale. Current approaches for eliminating cumulative drift are mainly based on …
Dual-branch CNNs for vehicle detection and tracking on LiDAR data
We present a novel vehicle detection and tracking system that works solely on 3D LiDAR
information. Our approach segments vehicles using a dual-view representation of the 3D …
information. Our approach segments vehicles using a dual-view representation of the 3D …
Limoseg: Real-time bird's eye view based lidar motion segmentation
Moving object detection and segmentation is an essential task in the Autonomous Driving
pipeline. Detecting and isolating static and moving components of a vehicle's surroundings …
pipeline. Detecting and isolating static and moving components of a vehicle's surroundings …
Augmented multiple vehicles' trajectories extraction under occlusions with roadside LiDAR data
Object occlusion is a common issue in Light Detection and Ranging (LiDAR)-based vehicle
tracking technology. The occlusions can cause variance in vehicle location and speed …
tracking technology. The occlusions can cause variance in vehicle location and speed …