SPBA-Net point cloud object detection with sparse attention and box aligning
Abstract Object detection in point clouds is essential for various applications, including autonomous navigation, household robots, and augmented/virtual reality. However, during voxelization and Bird’s Eye View transformation, local point cloud data often remains sparse due to non-target areas and...
Saved in:
| Main Authors: | Haojie Sha, Qingrui Gao, Hao Zeng, Kai Li, Wang Li, Xuande Zhang, Xiaohui Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-77097-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prob-sparse self-attention extraction of time-aligned dynamic functional connectivity for ASD diagnosis
by: Hongwu Chen, et al.
Published: (2025-01-01) -
All-weather precision alignment technology for ultra-wide steel box girders in cable-stayed bridges
by: Wang Laifa, et al.
Published: (2025-07-01) -
SURABHI: Self-Training Using Rectified Annotations-Based Hard Instances for Eidetic Cattle Recognition
by: Manu Ramesh, et al.
Published: (2024-11-01) -
Feature-Guided Instance Mining and Task-Aligned Focal Loss for Weakly Supervised Object Detection in Remote Sensing Images
by: Jinlin Tan, et al.
Published: (2025-05-01) -
GuidedBox: a segmentation-guided box teacher-student approach for weakly supervised road segmentation
by: Teerapong Panboonyuen, et al.
Published: (2025-12-01)