Attention-Based LiDAR–Camera Fusion for 3D Object Detection in Autonomous Driving
In multi-vehicle traffic scenarios, achieving accurate environmental perception and motion trajectory tracking through LiDAR–camera fusion is critical for downstream vehicle planning and control tasks. To address the challenges of cross-modal feature interaction in LiDAR–image fusion and the low rec...
Saved in:
Main Authors: | Zhibo Wang, Xiaoci Huang, Zhihao Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-05-01
|
Series: | World Electric Vehicle Journal |
Subjects: | |
Online Access: | https://www.mdpi.com/2032-6653/16/6/306 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Fusion of LiDAR Features for 3D Object Detection in Autonomous Driving
by: Mingrui Wang, et al.
Published: (2025-06-01) -
LiGenCam: Reconstruction of Color Camera Images from Multimodal LiDAR Data for Autonomous Driving
by: Minghao Xu, et al.
Published: (2025-07-01) -
Roadside LiDAR for C-ITS: placement, calibration, and fusion of perception
by: Changlong Zhang, et al.
Published: (2025-06-01) -
Trajectory-Based Road Autolabeling With Lidar-Camera Fusion in Winter Conditions
by: Eerik Alamikkotervo, et al.
Published: (2025-01-01) -
Onboard LiDAR–Camera Deployment Optimization for Pavement Marking Distress Fusion Detection
by: Ciyun Lin, et al.
Published: (2025-06-01)