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DOTA: A large-scale dataset for object detection in aerial images

Xia, Gui-Song and Bai, Xiang and Ding, Jian and Zhu, Zhen and Belongie, Serge and Luo, Jiebo and Datcu, Mihai and Pelillo, Marcello and Zhang, Liangpei (2018) DOTA: A large-scale dataset for object detection in aerial images. In: 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1-10. CVPR 2018, 18.-22. June 2018, Salt Lake City, Utah.

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Official URL: https://vision.cornell.edu/se3/wp-content/uploads/2018/03/2666.pdf

Abstract

Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge variation in the scale, orientation and shape of the object instances on the earth's surface, but also due to the scarcity of well-annotated datasets of objects in aerial scenes. To advance object detection research in Earth Vision, also known as Earth Observation and Remote Sensing, we introduce a large-scale Dataset for Object deTection in Aerial images (DOTA). To this end, we collect 2806 aerial images from different sensors and platforms. Each image is of the size about 4000-by-4000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes. These DOTA images are then annotated by experts in aerial image interpretation using 15 common object categories. The fully annotated DOTA images contains 188,282 instances, each of which is labeled by an arbitrary (8 d.o.f.) quadrilateral To build a baseline for object detection in Earth Vision, we evaluate state-of-the-art object detection algorithms on DOTA. Experiments demonstrate that DOTA well represents real Earth Vision applications and are quite challenging.

Item URL in elib:https://elib.dlr.de/123453/
Document Type:Conference or Workshop Item (Speech)
Title:DOTA: A large-scale dataset for object detection in aerial images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Xia, Gui-Songguisong.xia (at) whu.edu.cnUNSPECIFIED
Bai, XiangHuazhong University of Science and TechnologyUNSPECIFIED
Ding, JianWuhan UniversityUNSPECIFIED
Zhu, ZhenHuazhong University of Science and TechnologyUNSPECIFIED
Belongie, SergeCornell UniversityUNSPECIFIED
Luo, JieboRochester UniversityUNSPECIFIED
Datcu, MihaiMihai.Datcu (at) dlr.deUNSPECIFIED
Pelillo, MarcelloUniversity of VeniceUNSPECIFIED
Zhang, LiangpeiWuhan UniversityUNSPECIFIED
Date:June 2018
Journal or Publication Title:2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-10
Status:Published
Keywords:EO dataset, DOTA
Event Title:CVPR 2018
Event Location:Salt Lake City, Utah
Event Type:international Conference
Event Dates:18.-22. June 2018
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Dumitru, Corneliu Octavian
Deposited On:29 Nov 2018 10:50
Last Modified:31 Jul 2019 20:21

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