Computing systems for autonomous driving: State of the art and challenges
The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …
learning, and hardware acceleration) and the broad deployment of communication …
Ultra fast structure-aware deep lane detection
Modern methods mainly regard lane detection as a problem of pixel-wise segmentation,
which is struggling to address the problem of challenging scenarios and speed. Inspired by …
which is struggling to address the problem of challenging scenarios and speed. Inspired by …
Ultra fast deep lane detection with hybrid anchor driven ordinal classification
Modern methods mainly regard lane detection as a problem of pixel-wise segmentation,
which is struggling to address the problems of efficiency and challenging scenarios like …
which is struggling to address the problems of efficiency and challenging scenarios like …
Weakly supervised instance segmentation using the bounding box tightness prior
This paper presents a weakly supervised instance segmentation method that consumes
training data with tight bounding box annotations. The major difficulty lies in the uncertain …
training data with tight bounding box annotations. The major difficulty lies in the uncertain …
End-to-end lane marker detection via row-wise classification
In autonomous driving, detecting reliable and accurate lane marker positions is a crucial yet
challenging task. The conventional approaches for the lane marker detection problem …
challenging task. The conventional approaches for the lane marker detection problem …
Merizo: a rapid and accurate protein domain segmentation method using invariant point attention
Abstract The AlphaFold Protein Structure Database, containing predictions for over 200
million proteins, has been met with enthusiasm over its potential in enriching structural …
million proteins, has been met with enthusiasm over its potential in enriching structural …
Multitask attention network for lane detection and fitting
Many CNN-based segmentation methods have been applied in lane marking detection
recently and gain excellent success for a strong ability in modeling semantic information …
recently and gain excellent success for a strong ability in modeling semantic information …
Lane detection and classification using cascaded CNNs
Lane detection is extremely important for autonomous vehicles. For this reason, many
approaches use lane boundary information to locate the vehicle inside the street, or to …
approaches use lane boundary information to locate the vehicle inside the street, or to …
3d bird's-eye-view instance segmentation
Recent deep learning models achieve impressive results on 3D scene analysis tasks by
operating directly on unstructured point clouds. A lot of progress was made in the field of …
operating directly on unstructured point clouds. A lot of progress was made in the field of …
Lane line detection based on object feature distillation
M Haris, A Glowacz - Electronics, 2021 - mdpi.com
In order to meet the real-time requirements of the autonomous driving system, the existing
method directly up-samples the encoder's output feature map to pixel-wise prediction, thus …
method directly up-samples the encoder's output feature map to pixel-wise prediction, thus …