2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

TH1.R9.1

SELF-CONSTRUCTING GRAPH CONVOLUTIONAL NETWORKS FOR SEMANTIC LABELING

Qinghui Liu, Norwegian Computing Center, Norway; Michael Kampffmeyer, Robert Jenssen, UiT The Arctic University of Norway, Norway; Arnt-Børre Salberg, Norwegian Computing Center, Norway
Session:
Semantic Learning for Image Analysis
Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)
Presentation Time:
Thu, 1 Oct, 12:00-12:10 (UTC)
Thu, 1 Oct, 20:00-20:10 China Standard Time (UTC +8)
Thu, 1 Oct, 14:00-14:10 Central Europe Summer Time (UTC +2)
Thu, 1 Oct, 05:00-05:10 Pacific Daylight Time (UTC -7)
Session Co-Chairs:
Stefano Zorzi, TUGraz and Bohao Huang, Duke University
Session Managers:
Shashank S. Joshil and Na Liu

Presentation

Discussion

Resources

Session

TH1.R9.1: SELF-CONSTRUCTING GRAPH CONVOLUTIONAL NETWORKS FOR SEMANTIC LABELING
Qinghui Liu, Norwegian Computing Center, Norway; Michael Kampffmeyer, Robert Jenssen, UiT The Arctic University of Norway, Norway; Arnt-Børre Salberg, Norwegian Computing Center, Norway
TH1.R9.2: REGULARIZED BUILDING SEGMENTATION BY FRAME FIELD LEARNING
Nicolas Girard, Inria, France; Dmitriy Smirnov, Justin Solomon, Massachusetts Institute of Technology, United States; Yuliya Tarabalka, LuxCarta Technology, France
TH1.R9.3: LOOK AT THE BIG PICTURE: BUILDING AREA EXTRACTION WITH GLOBAL DENSITY MAP
Haowen Guo, Wuhan University, China; Tongyuan Zou, Space Star Technology Co., Ltd. (SST), China; Wensheng Cheng, Wen Yang, Guisong Xia, Wuhan University, China
TH1.R9.4: SEMANTIC SEGMENTATION REFINEMENT WITH DEEP EDGE SUPERPIXELS TO ENHANCE HISTORICAL LAND COVER
Rémi Ratajczak, Carlos Crispim-Junior, Laboratoire d'InfoRmatique en Image et Systèmes d'information, France; Béatrice Fervers, Centre Léon Bérard, France; Elodie Faure, Gustave Roussy, France; Laure Tougne, Laboratoire d'InfoRmatique en Image et Systèmes d'information, France
TH1.R9.5: A MODIFIED D-LINKNET WITH TRANSFER LEARNING FOR ROAD EXTRACTION FROM HIGH-RESOLUTION REMOTE SENSING
Yanan Zhang, Qiqi Zhu, China University of Geosciences, China; Yanfei Zhong, Wuhan University, China; Qingfeng Guan, China University of Geosciences, China; Liangpei Zhang, Deren Li, Wuhan University, China
TH1.R9.6: LEARNING DISCRIMINATIVE GLOBAL AND LOCAL FEATURES FOR BUILDING EXTRACTION FROM AERIAL IMAGES
Yue Liao, Hongyan Zhang, Guangyi Yang, Liangpei Zhang, Wuhan University, China
TH1.R9.7: DILATED RESIDUAL NETWORK BASED ON DUAL EXPECTATION MAXIMIZATION ATTENTION FOR SEMANTIC SEGMENTATION OF REMOTE SENSING IMAGES
Jiachao Liu, Xinyue Xiong, Jiaojiao Li, Chaoxiong Wu, Rui Song, Xidian University, China
TH1.R9.8: MAP-REPAIR: DEEP CADASTRE MAPS ALIGNMENT AND TEMPORAL INCONSISTENCIES FIX IN SATELLITE IMAGES
Stefano Zorzi, TUGraz, Austria; Ksenia Bittner, German Aerospace Center (DLR), Germany; Friedrich Fraundorfer, TUGraz, Austria
TH1.R9.9: SEMANTIC SEGMENTATION OF URBAN BUILDINGS FROM VHR REMOTELY SENSED IMAGERY USING ATTENTION-BASED CNN
Zhijie Zhang, Chuanrong Zhang, Weidong Li, University of Connecticut, United States
TH1.R9.10: SEMI2I: SEMANTICALLY CONSISTENT IMAGE-TO-IMAGE TRANSLATION FOR DOMAIN ADAPTATION OF REMOTE SENSING DATA
Onur Tasar, S L Happy, Yuliya Tarabalka, Pierre Alliez, INRIA, France
TH1.R9.11: Spatial Attention Network for Road Extraction
Ruonan Chen, Yuan Hu, Tong Wu, Ling Peng, Aerospace Information Research Institute, Chinese Academy of Sciences, China