In computer vision, significant advances have been made on object detection with the rapid
development of deep convolutional neural networks (CNN). This paper provides a …

Earth system science has changed rapidly due to global environmental changes and the
advent of Earth observation technology. Therefore, new tools are required to monitor …

We present an open-source toolbox, named MMRotate, which provides a coherent algorithm
framework of training, inferring, and evaluation for the popular rotated object detection …

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 …

The identification of small land targets in remote sensing imagery has emerged as a
significant research objective. Despite significant advancements in object detection …

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 …

Tiny object detection (TOD) in aerial images is challenging since a tiny object only contains
a few pixels. State-of-the-art object detectors do not provide satisfactory results on tiny …

With the vigorous development of computer vision, oriented object detection has gradually
been featured. In this paper, a novel differentiable angle coder named phase-shifting coder …

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 …

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 …