With the rapid development of object detection, it is widely used in many scenes and
images. However, the dense arrangement of objects with different dimensions, orientations …

With the advancement of maritime unmanned aerial vehicles (UAVs) and deep learning
technologies, the application of UAV-based object detection has become increasingly …

In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO
series and is easily extensible for many object recognition tasks such as instance …

Existing rotated object detectors are mostly inherited from the horizontal detection paradigm,
as the latter has evolved into a well-developed area. However, these detectors are difficult to …

Boundary discontinuity and its inconsistency to the final detection metric have been the
bottleneck for rotating detection regression loss design. In this paper, we propose a novel …

In contrast to the generic object, aerial targets are often non-axis aligned with arbitrary
orientations having the cluttered surroundings. Unlike the mainstreamed approaches …

The development of detection methods for oriented object detection remains a challenging
task. A considerable obstacle is the wide variation in the shape (eg, aspect ratio) of objects …

Detecting objects in remote sensing images (RSIs) using oriented bounding boxes (OBBs) is
flourishing but challenging, wherein the design of OBB representations is the key to …

Differing from the well-developed horizontal object detection area whereby the computing-
friendly IoU based loss is readily adopted and well fits with the detection metrics. In contrast …

Due to its great application value in the military and civilian fields, ship detection in synthetic
aperture radar (SAR) images has always attracted much attention. However, ship targets in …