In this work, we propose a neural network (NN) based solution to efficiently process radar data. We introduce RadarPCNN, an architecture specifically designed for performing semantic segmentation on radar point clouds. It uses PointNet $$++$$ + + as a building-block—enhancing the sampling ...
Semantic segmentation for LiDAR point clouds plays a crucial role in autonomous driving and robotic navigation. Currently, voxel-based methods have emerged as the predominant type of approaches in this domain. However, such methods inevi... X Wang,K Cui,L Wang,... - Chinese Conference on Patte...
Continual Semantic Segmentation With Automatic Memory Sample Selection Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation Hunting Sparsity: Density-Guided Contrastive Learning for Semi-Supervised Semantic Segmentation Open-Set Semantic Segmentation for Point Clouds via Adversarial ...
Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Clouds Semantic segmentation of 3D point cloud data is essential for enhanced high-level perception in autonomous platforms. Furthermore, given the increasing deployment of LiDAR sensors onboard of cars and drones, a special...
1. Introduction 3D semantic segmentation of LiDAR point clouds has played a key role in scene understanding, facilitating applications such as autonomous driving [6, 23, 26, 28, 46, 60, 63] and robotics [3, 38, 51, 52]. However, many contemporary meth- ods require rela...
Semantic segmentation of large-scale outdoor point clouds is essential for urban scene understanding in various applications, especially autonomous driving and urban high-definition (HD) mapping. With rapid developments of mobile laser scanning (MLS) systems, massive point clouds are available for scene...
Road segmentation with image-LiDAR data fusion in deep neural network Article 27 July 2019 Depth Estimation via Sparse Radar Prior and Driving Scene Semantics Chapter © 2023 A Cylindrical Convolution Network for Dense Top-View Semantic Segmentation with LiDAR Point Clouds Chapter © 2023 ...
Results of participants will be presented on the official H3D homepage (https://ifpwww.ifp.uni-stuttgart.de/benchmark/hessigheim/results.aspx) in order to reflect the state of the art of semantic segmentation of point clouds and meshes. 2.8. Evaluation metrics Semantic segmentation results ...
数据集:实验使用了三个数据集来验证TARSS-Net的性能,包括CARRADA、CARRADA-RAC和KuRALS。CARRADA是一个大规模的多视图标注雷达记录数据集,包含不同天气条件下的驾驶场景中的四类对象;CARRADA-RAC是CARRADA的改进版本,对RA视图进行了校准;KuRALS是一个大规模的自收集真实数据集,包含各种典型目标。 训练设置:所有模...
A list of radar and optical satellite datasets for ship detection, classification, semantic segmentation and instance segmentation tasks. - jasonmanesis/Satellite-Imagery-Datasets-Containing-Ships