Bounding Box Projection for Regression Uncertainty in Oriented Object Detection
Oriented object detection has recently attracted increasing attention for its importance in aerial image processing. Popular detection methods for oriented and densely packed objects usually utilize the rotation angle to reduce the overlap of bounding boxes over the horizontal line. However, those a...
Main Authors: | Qian Wu, Wangtao Xiang, Rui Tang, Jun Zhu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9400416/ |
Similar Items
-
A Scale Balanced Loss for Bounding Box Regression
by: Degang Sun, et al.
Published: (2020-01-01) -
Recalibrating Features and Regression for Oriented Object Detection
by: Weining Chen, et al.
Published: (2023-04-01) -
Corner-Point and Foreground-Area IoU Loss: Better Localization of Small Objects in Bounding Box Regression
by: Delong Cai, et al.
Published: (2023-05-01) -
Quadbox: Quadrilateral Bounding Box Based Scene Text Detection Using Vector Regression
by: Prateek Keserwani, et al.
Published: (2021-01-01) -
Fused-IoU Loss: Efficient Learning for Accurate Bounding Box Regression
by: Yong Sun, et al.
Published: (2024-01-01)