Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
Semantics for robotic mapping, perception and interaction: A survey
For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …
require a deeper understanding of the world in which they operate. In robotics and related …
Multimodal end-to-end autonomous driving
A crucial component of an autonomous vehicle (AV) is the artificial intelligence (AI) is able to
drive towards a desired destination. Today, there are different paradigms addressing the …
drive towards a desired destination. Today, there are different paradigms addressing the …
Deep learning serves traffic safety analysis: A forward‐looking review
This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …
Detecting unexpected obstacles for self-driving cars: Fusing deep learning and geometric modeling
The detection of small road hazards, such as lost cargo, is a vital capability for self-driving
cars. We tackle this challenging and rarely addressed problem with a vision system that …
cars. We tackle this challenging and rarely addressed problem with a vision system that …
Semantic stereo for incidental satellite images
M Bosch, K Foster, G Christie, S Wang… - 2019 IEEE Winter …, 2019 - ieeexplore.ieee.org
The increasingly common use of incidental satellite images for stereo reconstruction versus
rigidly tasked binocular or trinocular coincident collection is helping to enable timely global …
rigidly tasked binocular or trinocular coincident collection is helping to enable timely global …
Restricted deformable convolution-based road scene semantic segmentation using surround view cameras
Understanding the surrounding environment of the vehicle is still one of the challenges for
autonomous driving. This paper addresses 360-degree road scene semantic segmentation …
autonomous driving. This paper addresses 360-degree road scene semantic segmentation …
On offline evaluation of vision-based driving models
Autonomous driving models should ideally be evaluated by deploying them on a fleet of
physical vehicles in the real world. Unfortunately, this approach is not practical for the vast …
physical vehicles in the real world. Unfortunately, this approach is not practical for the vast …
The future of parking: A survey on automated valet parking with an outlook on high density parking
H Banzhaf, D Nienhüser, S Knoop… - 2017 IEEE Intelligent …, 2017 - ieeexplore.ieee.org
In the near future, humans will be relieved from parking. Major improvements in autonomous
driving allow the realization of automated valet parking (AVP). It enables the vehicle to drive …
driving allow the realization of automated valet parking (AVP). It enables the vehicle to drive …
A cross-season correspondence dataset for robust semantic segmentation
M Larsson, E Stenborg… - Proceedings of the …, 2019 - openaccess.thecvf.com
In this paper, we present a method to utilize 2D-2D point matches between images taken
during different image conditions to train a convolutional neural network for semantic …
during different image conditions to train a convolutional neural network for semantic …