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 …
Robust lane detection from continuous driving scenes using deep neural networks
Lane detection in driving scenes is an important module for autonomous vehicles and
advanced driver assistance systems. In recent years, many sophisticated lane detection …
advanced driver assistance systems. In recent years, many sophisticated lane detection …
Sne-roadseg: Incorporating surface normal information into semantic segmentation for accurate freespace detection
Freespace detection is an essential component of visual perception for self-driving cars. The
recent efforts made in data-fusion convolutional neural networks (CNNs) have significantly …
recent efforts made in data-fusion convolutional neural networks (CNNs) have significantly …
[HTML][HTML] Perception, planning, control, and coordination for autonomous vehicles
Autonomous vehicles are expected to play a key role in the future of urban transportation
systems, as they offer potential for additional safety, increased productivity, greater …
systems, as they offer potential for additional safety, increased productivity, greater …
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 …
Hierarchical trajectory planning of an autonomous car based on the integration of a sampling and an optimization method
This paper presents a hierarchical trajectory planning based on the integration of a sampling
and an optimization method for urban autonomous driving. To manage a complex driving …
and an optimization method for urban autonomous driving. To manage a complex driving …
Road anomaly detection by partial image reconstruction with segmentation coupling
We present a novel approach to the detection of unknown objects in the context of
autonomous driving. The problem is formulated as anomaly detection, since we assume that …
autonomous driving. The problem is formulated as anomaly detection, since we assume that …
A sensor-fusion drivable-region and lane-detection system for autonomous vehicle navigation in challenging road scenarios
Autonomous vehicle navigation is challenging since various types of road scenarios in real
urban environments have to be considered, particularly when only perception sensors are …
urban environments have to be considered, particularly when only perception sensors are …
RoadFormer: Duplex transformer for RGB-normal semantic road scene parsing
The recent advancements in deep convolutional neural networks have shown significant
promise in the domain of road scene parsing. Nevertheless, the existing works focus …
promise in the domain of road scene parsing. Nevertheless, the existing works focus …
Lost and found: detecting small road hazards for self-driving vehicles
Lost and Found: detecting small road hazards for self-driving vehicles Page 1 Lost and Found:
Detecting Small Road Hazards for Self-Driving Vehicles Peter Pinggera1,3,∗ , Sebastian …
Detecting Small Road Hazards for Self-Driving Vehicles Peter Pinggera1,3,∗ , Sebastian …