RCBi-CenterNet: An Absolute Pose Policy for 3D Object Detection in Autonomous Driving
3D Object detection is a critical mission of the perception system of a self-driving vehicle. Existing bounding box-based methods are hard to train due to the need to remove duplicated detections in the post-processing stage. In this paper, we propose a center point-based deep neural network (DNN) a...
Main Authors: | Kang An, Yixin Chen, Suhong Wang, Zhifeng Xiao |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-06-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/12/5621 |
Similar Items
-
Fruit Detection Using CenterNet
by: Zhao, Kun
Published: (2021) -
Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models
by: Zhe Lin, et al.
Published: (2021-07-01) -
An Improved CenterNet Model for Insulator Defect Detection Using Aerial Imagery
by: Li, Y., et al.
Published: (2022) -
An Enhanced Feature Pyramid Object Detection Network for Autonomous Driving
by: Yutian Wu, et al.
Published: (2019-10-01) -
A Novel Method for Measuring Drogue-UAV Relative Pose in Autonomous Aerial Refueling Based on Monocular Vision
by: Yuebo Ma, et al.
Published: (2019-01-01)