@inproceedings{66c5580fdffa43fb8915cc2c75190221,
title = "A Context-Aware Anchor-free Tiny Object Detector for Aerial Images",
abstract = "Object detection in aerial images is a task of predicting the target categories while locating the objects. Since the different categories of objects may have similar shapes and textures in aerial images, we propose context-aware layer to provide global and robust features for classification and regression branch. In addition, we propose the CentraBox to reduce unnecessary training samples during the training phase. We also propose the instance-level normalization to balance the contributions among the instances. Finally, we compare our method with other methods in terms of accuracy, speed and parameters usage. Moreover, we also compare our own method with different hyper-parameter settings.",
keywords = "Aerial image, Object detection, Self attention",
author = "Chen, {Li Syuan} and Way, {Der Lor} and Shih, {Zen Chung}",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; null ; Conference date: 04-01-2022 Through 06-01-2022",
year = "2022",
month = jan,
day = "4",
doi = "10.1117/12.2624186",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Masayuki Nakajima and Shogo Muramatsu and Jae-Gon Kim and Jing-Ming Guo and Qian Kemao",
booktitle = "International Workshop on Advanced Imaging Technology, IWAIT 2022",
address = "United States",
}