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 …

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 …

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 …

Recently, transformer-based methods have achieved promising progresses in object
detection, as they can eliminate the post-processes like NMS and enrich the deep …

Remote sensing object detection (RSOD), one of the most fundamental and challenging
tasks in the remote sensing field, has received long-standing attention. In recent years, deep …

Object detection in remote-sensing images is a crucial task in the fields of Earth observation
and computer vision. Despite impressive progress in modern remote-sensing object …

Recently, many arbitrary-oriented object detection (AOOD) methods have been proposed
and attracted widespread attention in many fields. However, most of them are based on …

Fine-grained oriented object recognition (FGO) is a practical need for intellectually
interpreting remote sensing images. It aims at realizing fine-grained classification and …

Oriented object detection in aerial images has received extensive attention due to its wide
range of application scenarios. Although great success has been achieved, current methods …

Text spotting end-to-end methods have recently gained attention in the literature due to the
benefits of jointly optimizing the text detection and recognition components. Existing …