An Empirical Study of Methods for Small Object Detection from Satellite Imagery
Computer Vision and Pattern Recognition
2026-01-01 v2 Artificial Intelligence
Abstract
This paper reviews object detection methods for finding small objects from remote sensing imagery and provides an empirical evaluation of four state-of-the-art methods to gain insights into method performance and technical challenges. In particular, we use car detection from urban satellite images and bee box detection from satellite images of agricultural lands as application scenarios. Drawing from the existing surveys and literature, we identify several top-performing methods for the empirical study. Public, high-resolution satellite image datasets are used in our experiments.
Cite
@article{arxiv.2502.03674,
title = {An Empirical Study of Methods for Small Object Detection from Satellite Imagery},
author = {Xiaohui Yuan and Aniv Chakravarty and Lichuan Gu and Zhenchun Wei and Elinor Lichtenberg and Tian Chen},
journal= {arXiv preprint arXiv:2502.03674},
year = {2026}
}