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Found 2 papers, 2 papers with code
Optimization for Arbitrary-Oriented Object Detection via Representation Invariance Loss
In this paper, we propose a Representation Invariance Loss (RIL) to optimize the bounding box regression for the rotating objects.
Ranked #27 on
Object Detection In Aerial Images
on DOTA
(using extra training data)
CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images
The proposed framework creates more powerful semantic representations for objects in remote sensing images and achieves high-performance real-time object detection.
Ranked #44 on
Object Detection In Aerial Images
on DOTA
(using extra training data)
