Small Object Detection (SOD) is an important machine vision topic because (i) a variety of real-world applications require object detection for distant objects and (ii) SOD is a challenging task due to the noisy, blurred, and less-informative image appearances of small objects. This paper proposes a new SOD dataset consisting of 39,070 images including 137,121 bird instances, which is called the Small Object Detection for Spotting Birds (SOD4SB) dataset. The detail of the challenge with the SOD4SB dataset is introduced in this paper. In total, 223 participants joined this challenge. This paper briefly introduces the award-winning methods. The dataset, the baseline code, and the website for evaluation on the public testset are publicly available.

翻译：小目标检测（SOD）是机器视觉领域的重要课题，原因在于：（i）诸多实际应用需要检测远距离物体；（ii）小目标图像特征存在噪声、模糊且信息量不足等问题，使得该任务极具挑战性。本文提出了一个包含39,070张图像、137,121个鸟类实例的新SOD数据集，命名为"鸟类识别小目标检测数据集"（SOD4SB）。本文详细介绍了基于SOD4SB数据集的挑战赛设置。共有223名参赛者参与本次挑战，本文简要介绍了获奖方法。该数据集、基线代码以及公共测试集评估网站均已公开。