3D object detection for autonomous driving: A comprehensive survey
Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
Deep learning-based perception systems for autonomous driving: A comprehensive survey
With the rapid development of society and the economy, autonomous driving techniques are
widely applied in many areas, such as autonomous vehicles, autonomous drones, and …
widely applied in many areas, such as autonomous vehicles, autonomous drones, and …
[HTML][HTML] 基于深度学习的视觉目标检测技术综述
曹家乐， 李亚利， 孙汉卿， 谢今， 黄凯奇， 庞彦伟 - 2022 - cjig.cn
摘要视觉目标检测旨在定位和识别图像中存在的物体, 属于计算机视觉领域的经典任务之一,
也是许多计算机视觉任务的前提与基础, 在自动驾驶, 视频监控等领域具有重要的应用价值 …
也是许多计算机视觉任务的前提与基础, 在自动驾驶, 视频监控等领域具有重要的应用价值 …
Spg: Unsupervised domain adaptation for 3d object detection via semantic point generation
In autonomous driving, a LiDAR-based object detector should perform reliably at different
geographic locations and under various weather conditions. While recent 3D detection …
geographic locations and under various weather conditions. While recent 3D detection …
Cross-modality knowledge distillation network for monocular 3d object detection
Y Hong, H Dai, Y Ding - European Conference on Computer Vision, 2022 - Springer
Leveraging LiDAR-based detectors or real LiDAR point data to guide monocular 3D
detection has brought significant improvement, eg, Pseudo-LiDAR methods. However, the …
detection has brought significant improvement, eg, Pseudo-LiDAR methods. However, the …
Disparity-based multiscale fusion network for transportation detection
J Chen, Q Wang, W Peng, H Xu, X Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The transportation detection of long-distance small objects has low accuracy. In this work,
we propose DMF, which is based on disparity depths. We map different disparity regions to …
we propose DMF, which is based on disparity depths. We map different disparity regions to …
Monocular 3d object detection with depth from motion
Perceiving 3D objects from monocular inputs is crucial for robotic systems, given its
economy compared to multi-sensor settings. It is notably difficult as a single image can not …
economy compared to multi-sensor settings. It is notably difficult as a single image can not …
End-to-end pseudo-lidar for image-based 3d object detection
Reliable and accurate 3D object detection is a necessity for safe autonomous driving.
Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment …
Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment …
Dsgn: Deep stereo geometry network for 3d object detection
Most state-of-the-art 3D object detectors rely heavily on LiDAR sensors and there remains a
large gap in terms of performance between image-based and LiDAR-based methods …
large gap in terms of performance between image-based and LiDAR-based methods …
Train in germany, test in the usa: Making 3d object detectors generalize
In the domain of autonomous driving, deep learning has substantially improved the 3D
object detection accuracy for LiDAR and stereo camera data alike. While deep networks are …
object detection accuracy for LiDAR and stereo camera data alike. While deep networks are …