Aerial object detection, as object detection in aerial images captured from an overhead
perspective, has been widely applied in urban management, industrial inspection, and other …

Nuclei detection is one of the most fundamental and challenging problems in
histopathological image analysis, which can localize nuclei to provide effective computer …

In this work, by re-examining the “matching” nature of Anomaly Detection (AD), we propose
a novel AD framework that simultaneously enjoys new records of AD accuracy and …

Oriented object detection, an emerging task in recent years, aims to identify and locate
objects across varied orientations. This requires the detector to accurately capture the …

Object detection in remote sensing images (RSIs) often suffers from several increasing
challenges including the large variation in object scales and the diverse-ranging context …

Cities play an important role in achieving sustainable development goals (SDGs) to promote
economic growth and meet social needs. Especially satellite imagery is a potential data …

In recent years, the Dataset for Object deTection in Aerial images (DOTA) dataset has
played a pivotal role in advancing object detection in aerial images (ODAI). Despite its …

Arbitrary-oriented object detection (AOOD) has been widely applied to locate and classify
objects with diverse orientations in remote sensing images. However, the inconsistent …

This paper introduces the point-axis representation for oriented object detection, as depicted
in aerial images in Fig. 1, emphasizing its flexibility and geometrically intuitive nature with …

Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing
various image interpretation tasks. Pretraining is an active research topic, encompassing …