MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results

2023 18th International Conference on Machine Vision and Applications (MVA) Pub Date : 2023-07-18 DOI:10.23919/MVA57639.2023.10215935

Yuki Kondo, N. Ukita, Takayuki Yamaguchi, Haoran Hou, Mu-Yi Shen, Chia-Chi Hsu, En-Ming Huang, Yu-Chen Huang, Yuelong Xia, Chien-Yao Wang, Chun-Yi Lee, Da Huo, Marc A. Kastner, Tingwei Liu, Yasutomo Kawanishi, Takatsugu Hirayama, Takahiro Komamizu, I. Ide, Yosuke Shinya, Xinyao Liu, Guang Liang, S. Yasui

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引用次数: 3

Abstract

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 1 is introduced in this paper. In total, 223 participants joined this challenge. This paper briefly introduces the award-winning methods. The dataset 2, the baseline code 3, and the website for evaluation on the public testset 4 are publicly available.

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MVA2023小目标检测挑战:数据集，方法和结果

小物体检测(SOD)是一个重要的机器视觉主题，因为(i)各种现实世界的应用需要对远处物体进行物体检测，(ii)由于小物体的噪声、模糊和信息较少的图像外观，SOD是一项具有挑战性的任务。本文提出了一个新的SOD数据集，该数据集由39070张图像组成，其中包含137121个鸟类实例，称为SOD4SB (Small Object Detection for Spotting Birds)数据集。本文详细介绍了SOD4SB数据集1的挑战。总共有223名参与者参加了这项挑战。本文简要介绍了获奖方法。数据集2、基线代码3和用于评估公共测试集4的网站是公开可用的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2023 18th International Conference on Machine Vision and Applications (MVA)

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