An efficient transformer for simultaneous learning of BEV and lane representations in 3D lane detection
Accurately detecting lane lines in 3D space is crucial for autonomous driving. Existing
methods usually first transform image-view features into bird-eye-view (BEV) by aid of …
methods usually first transform image-view features into bird-eye-view (BEV) by aid of …
Hierarchical road topology learning for urban mapless driving
The majority of current approaches in autonomous driving rely on High-Definition (HD) maps
which detail the road geometry and surrounding area. Yet, this reliance is one of the …
which detail the road geometry and surrounding area. Yet, this reliance is one of the …
Navigable Areas Segmentation Method for Unmanned Surface Vehicles in Paddy Fields
K Machida, T Nakamura, J Cai… - 2023 IEEE 11th …, 2023 - ieeexplore.ieee.org
An Unmanned Surface Vehicle (USV) capable of automatic navigation in paddy fields could
enhance paddy rice cultivation efficiency. However, flexible navigation is challenging with …
enhance paddy rice cultivation efficiency. However, flexible navigation is challenging with …
Deep learning for road area semantic segmentation in multispectral lidar data
J Taher - 2019 - aaltodoc.aalto.fi
Robust scene understanding is one of the main keys for safe autonomous vehicles and for
competent advanced driver assistance systems. Deep neural networks are powerful tools for …
competent advanced driver assistance systems. Deep neural networks are powerful tools for …
Real-Time Lane ID Estimation Using Recurrent Neural Networks With Dual Convention
I Halfaoui, F Bouzaraa, O Urfalioglu… - arXiv preprint arXiv …, 2020 - arxiv.org
Acquiring information about the road lane structure is a crucial step for autonomous
navigation. To this end, several approaches tackle this task from different perspectives such …
navigation. To this end, several approaches tackle this task from different perspectives such …