@inproceedings{b8fe47fa170d420b89514b7350067932,
title = "Effective Feature Enhancement and Model Ensemble Strategies in Tiny Object Detection",
abstract = "We introduce a novel tiny-object detection network that achieves better accuracy than existing detectors on TinyPerson dataset. It is an end-to-end detection framework developed on PaddlePaddle. A suit of strategies are developed to improve the detectors performance including: 1) data augmentation based on scale-match that aligns the object scales between the existing large-scale dataset and TinyPerson; 2) comprehensive training methods to further improve detection performance by a large margin; 3) model refinement based on the enhanced PAFPN module to fully utilize semantic information; 4) a hierarchical coarse-to-fine ensemble strategy to improve detection performance based on a well-designed model pond.",
keywords = "Data augmentation, Feature pyramid, Model ensemble",
author = "Yuan Feng and Xiaodi Wang and Ying Xin and Bin Zhang and Jingwei Liu and Mingyuan Mao and Sheng Xu and Baochang Zhang and Shumin Han",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 ; Conference date: 23-08-2020 Through 28-08-2020",
year = "2020",
doi = "10.1007/978-3-030-68238-5\_24",
language = "英语",
isbn = "9783030682378",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "324--330",
editor = "Adrien Bartoli and Andrea Fusiello",
booktitle = "Computer Vision – ECCV 2020 Workshops, Proceedings",
address = "德国",
}