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 …
Multi-radar inertial odometry for 3d state estimation using mmwave imaging radar
State estimation is a crucial component for the successful implementation of robotic systems,
relying on sensors such as cameras, LiDAR, and IMUs. However, in real-world scenarios …
relying on sensors such as cameras, LiDAR, and IMUs. However, in real-world scenarios …
TileMask: A Passive-Reflection-based Attack against mmWave Radar Object Detection in Autonomous Driving
In autonomous driving, millimeter wave (mmWave) radar has been widely adopted for object
detection because of its robustness and reliability under various weather and lighting …
detection because of its robustness and reliability under various weather and lighting …
RadarFormer: Lightweight and accurate real-time radar object detection model
The performance of perception systems developed for autonomous driving vehicles has
seen significant improvements over the last few years. This improvement was associated …
seen significant improvements over the last few years. This improvement was associated …
Camera-radar perception for autonomous vehicles and ADAS: Concepts, datasets and metrics
FM Barbosa, FS Osório - arXiv preprint arXiv:2303.04302, 2023 - arxiv.org
One of the main paths towards the reduction of traffic accidents is the increase in vehicle
safety through driver assistance systems or even systems with a complete level of autonomy …
safety through driver assistance systems or even systems with a complete level of autonomy …
Vision meets mmwave radar: 3d object perception benchmark for autonomous driving
Sensor fusion is crucial for an accurate and robust perception system on autonomous
vehicles. Most existing datasets and perception solutions focus on fusing cameras and …
vehicles. Most existing datasets and perception solutions focus on fusing cameras and …
Non-GDANets: Sports small object detection of thermal images with Non-Glodal decoupled Attention
J Zhao, B Mao, H Meng, L Wu, J Li - Plos one, 2022 - journals.plos.org
Because thermal infrared sport targets have rich and complex semantic information, there is
a high coupling between different types of features. In view of these limitations, we propose …
a high coupling between different types of features. In view of these limitations, we propose …
Budget-Aware Pruning: Handling Multiple Domains with Less Parameters
Deep learning has achieved state-of-the-art performance on several computer vision tasks
and domains. Nevertheless, it still has a high computational cost and demands a significant …
and domains. Nevertheless, it still has a high computational cost and demands a significant …
[图书][B] Modeling and Enhancing Deep Learning Accuracy in Computer Vision Applications
HR Hamandi - 2022 - search.proquest.com
Despite their wide usage in a tremendous number of applications, Computer Vision (CV)
algorithms struggle to maintain constant performance under varying image/video qualities …
algorithms struggle to maintain constant performance under varying image/video qualities …
Budget-Aware Pruning for Multi-Domain Learning
Deep learning has achieved state-of-the-art performance on several computer vision tasks
and domains. Nevertheless, it still has a high computational cost and demands a significant …
and domains. Nevertheless, it still has a high computational cost and demands a significant …