A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …
order to achieve robust and accurate scene understanding, autonomous vehicles are …
[HTML][HTML] A survey of uncertainty in deep neural networks
Over the last decade, neural networks have reached almost every field of science and
become a crucial part of various real world applications. Due to the increasing spread …
become a crucial part of various real world applications. Due to the increasing spread …
Dynamic anchor learning for arbitrary-oriented object detection
Arbitrary-oriented objects widely appear in natural scenes, aerial photographs, remote
sensing images, etc., and thus arbitrary-oriented object detection has received considerable …
sensing images, etc., and thus arbitrary-oriented object detection has received considerable …
Gaussian yolov3: An accurate and fast object detector using localization uncertainty for autonomous driving
The use of object detection algorithms is becoming increasingly important in autonomous
vehicles, and object detection at high accuracy and a fast inference speed is essential for …
vehicles, and object detection at high accuracy and a fast inference speed is essential for …
A survey on 3d object detection methods for autonomous driving applications
An autonomous vehicle (AV) requires an accurate perception of its surrounding environment
to operate reliably. The perception system of an AV, which normally employs machine …
to operate reliably. The perception system of an AV, which normally employs machine …
A review and comparative study on probabilistic object detection in autonomous driving
Capturing uncertainty in object detection is indispensable for safe autonomous driving. In
recent years, deep learning has become the de-facto approach for object detection, and …
recent years, deep learning has become the de-facto approach for object detection, and …
Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds
T Cortinhal, G Tzelepis, E Erdal Aksoy - … , ISVC 2020, San Diego, CA, USA …, 2020 - Springer
In this paper, we introduce SalsaNext for the uncertainty-aware semantic segmentation of a
full 3D LiDAR point cloud in real-time. SalsaNext is the next version of SalsaNet 1 which has …
full 3D LiDAR point cloud in real-time. SalsaNext is the next version of SalsaNet 1 which has …
Bounding box regression with uncertainty for accurate object detection
Large-scale object detection datasets (eg, MS-COCO) try to define the ground truth
bounding boxes as clear as possible. However, we observe that ambiguities are still …
bounding boxes as clear as possible. However, we observe that ambiguities are still …
Lasernet: An efficient probabilistic 3d object detector for autonomous driving
In this paper, we present LaserNet, a computationally efficient method for 3D object
detection from LiDAR data for autonomous driving. The efficiency results from processing …
detection from LiDAR data for autonomous driving. The efficiency results from processing …