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Counting dense objects in remote sensing images

Abstract: 

Estimating accurate number of interested objects from a given image is a challenging yet important task. Significant efforts have been made to address this problem and achieve great progress, yet counting number of ground objects from remote sensing images is barely studied. In this paper, we are interested in counting dense objects from remote sensing images. Compared with object counting in natural scene, this task is challenging in following factors: large scale variation, complex cluttered background and orientation arbitrariness. More importantly, the scarcity of data severely limits the development of research in this field. To address these issues, we first construct a large-scale object counting dataset based on remote sensing images, which contains four kinds of objects: buildings, crowded ships in harbor, large-vehicles and small-vehicles in parking lot. We then benchmark the dataset by designing a novel neural network which can generate density map of an input image. The proposed network consists of three parts namely convolution block attention module (CBAM), scale pyramid module (SPM) and deformable convolution module (DCM). Experiments on the proposed dataset and comparisons with state of the art methods demonstrate the challenging of the proposed dataset, and superiority and effectiveness of our method.

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Paper Details

Authors:
Guangshuai Gao, Qingjie Liu, Yunhong Wang
Submitted On:
10 February 2020 - 11:09pm
Short Link:
Type:
Poster
Event:
Presenter's Name:
Guangshuai Gao
Paper Code:
4709
Document Year:
2020
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[1] Guangshuai Gao, Qingjie Liu, Yunhong Wang, "Counting dense objects in remote sensing images", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/4976. Accessed: Jun. 07, 2020.
@article{4976-20,
url = {http://sigport.org/4976},
author = {Guangshuai Gao; Qingjie Liu; Yunhong Wang },
publisher = {IEEE SigPort},
title = {Counting dense objects in remote sensing images},
year = {2020} }
TY - EJOUR
T1 - Counting dense objects in remote sensing images
AU - Guangshuai Gao; Qingjie Liu; Yunhong Wang
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/4976
ER -
Guangshuai Gao, Qingjie Liu, Yunhong Wang. (2020). Counting dense objects in remote sensing images. IEEE SigPort. http://sigport.org/4976
Guangshuai Gao, Qingjie Liu, Yunhong Wang, 2020. Counting dense objects in remote sensing images. Available at: http://sigport.org/4976.
Guangshuai Gao, Qingjie Liu, Yunhong Wang. (2020). "Counting dense objects in remote sensing images." Web.
1. Guangshuai Gao, Qingjie Liu, Yunhong Wang. Counting dense objects in remote sensing images [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/4976