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 …
Vehicle detection for autonomous driving: A review of algorithms and datasets
J Karangwa, J Liu, Z Zeng - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Nowadays, vehicles with a high level of automation are being driven everywhere. With the
apparent success of autonomous driving technology, we keep working to achieve fully …
apparent success of autonomous driving technology, we keep working to achieve fully …
VP-Net: Voxels as points for 3-D object detection
The 3-D object detection with light detection and ranging (LiDAR) point clouds is a
challenging problem, which requires 3-D scene understanding, yet this task is critical to …
challenging problem, which requires 3-D scene understanding, yet this task is critical to …
Semantic segmentation of bridge point clouds with a synthetic data augmentation strategy and graph-structured deep metric learning
Deep learning techniques are capable of providing versatile solutions to automate
classification of bridge point clouds into corresponding constituent components, but training …
classification of bridge point clouds into corresponding constituent components, but training …
Stereodistill: Pick the cream from lidar for distilling stereo-based 3d object detection
In this paper, we propose a cross-modal distillation method named StereoDistill to narrow
the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors …
the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors …
AnchorPoint: Query design for transformer-based 3D object detection and tracking
With the success of Transformers in natural language processing, object detection with
Transformers (DETR) has attracted widespread attentions. In previous Transformer-based …
Transformers (DETR) has attracted widespread attentions. In previous Transformer-based …
Focal Distillation From High-Resolution Data to Low-Resolution Data for 3D Object Detection
LiDAR-based 3D object detection plays an essential role in autonomous driving. Although
the detector trained on high-resolution data has much better performance than the same …
the detector trained on high-resolution data has much better performance than the same …
Impdet: Exploring implicit fields for 3d object detection
Conventional 3D object detection approaches concentrate on bounding boxes
representation learning with several parameters, ie, localization, dimension, and orientation …
representation learning with several parameters, ie, localization, dimension, and orientation …
Survey on deep learning-based 3D object detection in autonomous driving
Z Liang, Y Huang - … of the Institute of Measurement and …, 2023 - journals.sagepub.com
Autonomous driving technology has entered into the fast lane of development in recent
years. An essential component of autonomous driving technology is scene perception …
years. An essential component of autonomous driving technology is scene perception …
SFSS-Net: shape-awared filter and sematic-ranked sampler for voxel-based 3D object detection
L Zhu, Z Chen, B Wang, G Tian, L Ji - Neural Computing and Applications, 2023 - Springer
Abstract 3D object detection has been used in many fields, such as virtual reality, automatic
driving and target tracking. 3D object detection methods usually use point clouds as input …
driving and target tracking. 3D object detection methods usually use point clouds as input …