Dataset for small object detection with shadow (SODwS)

Abstract

Detecting small objects in aerial images poses several challenges, including issues with resolution limitations, scale variability, background clutter, and object occlusion. Annotated datasets for small objects in aerial images are often scarce, complicating the training and validation of detection models. This article introduces a new dataset specifically designed for small object detection in low-altitude aerial images. It addresses the challenges posed by shadows, including their impact on object visibility, by including images that capture small objects obscured with shadows. The dataset also features ground-truth shadow maps to support research in shadow detection. This dataset offers potential for future research and serves as a resource for transfer learning.