Commonroad scenario designer: An open-source toolbox for map conversion and scenario creation for autonomous vehicles
S Maierhofer, M Klischat… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Maps are essential for testing autonomous driving functions. Several map and scenario
formats are available. However, they are usually not compatible with each other, limiting …
formats are available. However, they are usually not compatible with each other, limiting …
Skyscapes fine-grained semantic understanding of aerial scenes
Understanding the complex urban infrastructure with centimeter-level accuracy is essential
for many applications from autonomous driving to mapping, infrastructure monitoring, and …
for many applications from autonomous driving to mapping, infrastructure monitoring, and …
Adaptive effective receptive field convolution for semantic segmentation of VHR remote sensing images
Convolutional neural networks (CNNs) have facilitated impressive improvements in the
semantic segmentation of very high-resolution (VHR) remote sensing images. The success …
semantic segmentation of very high-resolution (VHR) remote sensing images. The success …
High-definition map generation technologies for autonomous driving
Z Bao, S Hossain, H Lang, X Lin - arXiv preprint arXiv:2206.05400, 2022 - arxiv.org
Autonomous driving has been among the most popular and challenging topics in the past
few years. On the road to achieving full autonomy, researchers have utilized various …
few years. On the road to achieving full autonomy, researchers have utilized various …
Intensity thresholding and deep learning based lane marking extraction and lane width estimation from mobile light detection and ranging (LiDAR) point clouds
Lane markings are one of the essential elements of road information, which is useful for a
wide range of transportation applications. Several studies have been conducted to extract …
wide range of transportation applications. Several studies have been conducted to extract …
2dsegformer: 2-d transformer model for semantic segmentation on aerial images
Two-dimensional position information of input tokens is essential for transformer-based
semantic segmentation models, especially on high-resolution aerial images. However …
semantic segmentation models, especially on high-resolution aerial images. However …
Lane detection: A survey with new results
Lane detection is essential for many aspects of autonomous driving, such as lane-based
navigation and high-definition (HD) map modeling. Although lane detection is challenging …
navigation and high-definition (HD) map modeling. Although lane detection is challenging …
A comprehensive review on lane marking detection using deep neural networks
Lane marking recognition is one of the most crucial features for automotive vehicles as it is
one of the most fundamental requirements of all the autonomy features of Advanced Driver …
one of the most fundamental requirements of all the autonomy features of Advanced Driver …
Interactive attention learning on detection of lane and lane marking on the road by monocular camera image
Vision-based identification of lane area and lane marking on the road is an indispensable
function for intelligent driving vehicles, especially for localization, mapping and planning …
function for intelligent driving vehicles, especially for localization, mapping and planning …
An optimized deep neural network detecting small and narrow rectangular objects in Google Earth images
Object detection is an important task for rapidly localizing target objects using high-
resolution satellite imagery (HRSI). Although deep learning has been shown an efficient …
resolution satellite imagery (HRSI). Although deep learning has been shown an efficient …