MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results
Journal
2023 18th International Conference on Machine Vision and Applications (MVA)
Part Of
Proceedings of MVA 2023 - 18th International Conference on Machine Vision and Applications
ISBN (of the container)
978-488552343-4
Date Issued
2023-07-23
Author(s)
Yuki Kondo
Norimichi Ukita
Takayuki Yamaguchi
Hao-Yu Hou
Mu-Yi Shen
Chia-Chi Hsu
En-Ming Huang
Yu-Chen Huang
Yu-Cheng Xia
Chien-Yao Wang
Da Huo
Marc A. Kastner
Tingwei Liu
Yasutomo Kawanishi
Takatsugu Hirayama
Takahiro Komamizu
Ichiro Ide
Yosuke Shinya
Xinyao Liu
Guang Liang
Syusuke Yasui
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.
Event(s)
18th International Conference on Machine Vision and Applications, MVA 2023
Publisher
IEEE
Type
conference paper