Towards deep radar perception for autonomous driving: Datasets, methods, and challenges
With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …
The next generation of 4D radar can achieve imaging capability in the form of high …
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 …
Pandaset: Advanced sensor suite dataset for autonomous driving
The accelerating development of autonomous driving technology has placed greater
demands on obtaining large amounts of high-quality data. Representative, labeled, real …
demands on obtaining large amounts of high-quality data. Representative, labeled, real …
Few-shot object counting and detection
We tackle a new task of few-shot object counting and detection. Given a few exemplar
bounding boxes of a target object class, we seek to count and detect all objects of the target …
bounding boxes of a target object class, we seek to count and detect all objects of the target …
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns
Monitoring the integrity of object detection for errors within the perception module of
automated driving systems (ADS) is paramount for ensuring safety. Despite recent …
automated driving systems (ADS) is paramount for ensuring safety. Despite recent …
Real-time object detection and recognition using fixed-wing Lale VTOL UAV
This research aimed to identify objects from a real-time video (30 Hz) stream transmitted
from a low-altitude long-endurance (LALE) fixed-wing hybrid vertical takeoff and landing …
from a low-altitude long-endurance (LALE) fixed-wing hybrid vertical takeoff and landing …
Jaccard metric losses: Optimizing the jaccard index with soft labels
Abstract Intersection over Union (IoU) losses are surrogates that directly optimize the
Jaccard index. Leveraging IoU losses as part of the loss function have demonstrated …
Jaccard index. Leveraging IoU losses as part of the loss function have demonstrated …
Bayesian deep learning for affordance segmentation in images
L Mur-Labadia, R Martinez-Cantin… - … on Robotics and …, 2023 - ieeexplore.ieee.org
Affordances are a fundamental concept in robotics since they relate available actions for an
agent depending on its sensory-motor capabilities and the environment. We present a novel …
agent depending on its sensory-motor capabilities and the environment. We present a novel …
A simple and efficient multi-task network for 3d object detection and road understanding
Detecting dynamic objects and predicting static road information such as drivable areas and
ground heights are crucial for safe autonomous driving. Previous works studied each …
ground heights are crucial for safe autonomous driving. Previous works studied each …
Real-time evaluation of perception uncertainty and validity verification of autonomous driving
Deep neural network algorithms have achieved impressive performance in object detection.
Real-time evaluation of perception uncertainty from deep neural network algorithms is …
Real-time evaluation of perception uncertainty from deep neural network algorithms is …