@inproceedings{ed7649bf22534480a81569bb72f3c6db,
title = "Horizontal Feature Pyramid Network for Object Detection in UAV Images",
abstract = "Feature extraction for object detection in UAV images is of great importance. In this context, a method named Horizontal Feature Pyramid Network (HFPN) is proposed, aiming at generating abundant features from the original Feature Pyramid Network (FPN). Specifically, we enhance the entire feature hierarchy with multiple stages of simple convolution and channel-wise addition operations, which enrich the classification and location information, and reduce the amount of computation. The detection accuracy on UAV image dataset VisDrone is improved with the proposed method.",
keywords = "HFPN (Horizontal Feature Pyramid Network), UAV, VisDrone, computer vision, object detection",
author = "Weiqian Tang and Jian Sun and Gang Wang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 China Automation Congress, CAC 2021 ; Conference date: 22-10-2021 Through 24-10-2021",
year = "2021",
doi = "10.1109/CAC53003.2021.9727887",
language = "English",
series = "Proceeding - 2021 China Automation Congress, CAC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7746--7750",
booktitle = "Proceeding - 2021 China Automation Congress, CAC 2021",
address = "United States",
}