TU2.R18.1

EVENT AND ACTIVITY RECOGNITION IN AERIAL VIDEOS USING DEEP NEURAL NETWORKS AND A NEW DATASET

Lichao Mou, Yuansheng Hua, German Aerospace Center (DLR); Technical University of Munich (TUM), Germany; Pu Jin, Technical University of Munich (TUM), Germany; Xiao Xiang Zhu, German Aerospace Center (DLR); Technical University of Munich (TUM), Germany

Session:
Detection and Segmentation using Very High Resolution Imaging

Track:
Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

Presentation Time:
Tue, 29 Sep, 14:30-14:40 (UTC)
Tue, 29 Sep, 22:30-22:40 China Standard Time (UTC +8)
Tue, 29 Sep, 16:30-16:40 Central Europe Summer Time (UTC +2)
Tue, 29 Sep, 07:30-07:40 Pacific Daylight Time (UTC -7)

Session Co-Chairs:
Stefania Matteoli, CNR and Silvia Liberata Ullo, University of Sannio
Session Managers:
Rosa Correa Pabón and Durga Nanda Yadav

Presentation

Discussion

Resources

Session

TU2.R18.1: EVENT AND ACTIVITY RECOGNITION IN AERIAL VIDEOS USING DEEP NEURAL NETWORKS AND A NEW DATASET
Lichao Mou, Yuansheng Hua, German Aerospace Center (DLR); Technical University of Munich (TUM), Germany; Pu Jin, Technical University of Munich (TUM), Germany; Xiao Xiang Zhu, German Aerospace Center (DLR); Technical University of Munich (TUM), Germany
TU2.R18.2: REMOTE SENSING TARGET TRACKING FOR UAV AERIAL VIDEOS BASED ON MULTI-FREQUENCY FEATURE ENHANCEMENT
Fukun Bi, Jiayi Sun, Mingyang Lei, Yanping Wang, Xiaodi Sun, North China University of Technology, China
TU2.R18.3: AN END-TO-END SCALABLE OBJECT DETECTION NETWORK FOR REMOTE SENSING IMAGES
Yani Duan, Zhu Teng, Baopeng Zhang, Beijing Jiaotong University, China; Jianping Fan, Lenovo Research, China
TU2.R18.4: ARBITRARY-ORIENTED SHIP DETECTION METHOD BASED ON IMPROVED REGRESSION MODEL FOR TARGET DIRECTION DETECTION NETWORK
Bohao Ran, Yanan You, Zezhong Li, Fang Liu, Beijing University of Posts and Telecommunications, China
TU2.R18.5: SHIP DETECTION FOR KOMPSAT-3A OPTICAL IMAGES USING BINARY FEATURES AND ADABOOST CLASSIFICATION
Jae Young Chang, Han Oh, Seung-Jae Lee, Kwang Jae Lee, Korea Aerospace Research Institute, Korea (South)
TU2.R18.6: Inshore Ship Detection based on Multi-Information Fusion Network and Instance Segmentation
Tian Tian, China University of Geosciences, China; Peng Gao, Zhihong Pan, Huazhong University of Science and Technology, China; Hang Li, Beijing Aerospace System Engineering Research Institute, China; Lizhe Wang, China University of Geosciences, China
TU2.R18.7: LEVEE-CRACK DETECTION FROM SATELLITE OR DRONE IMAGERY USING MACHINE LEARNING APPROACHES
Aditi Kuchi, Md Tamjidul Hoque, Mahdi Abdelguerfi, University of New Orleans, United States; Maik Flanagin, US Army Corps of Engineers, United States
TU2.R18.8: INSTANCE-AWARE REMOTE SENSING IMAGE CAPTIONING WITH CROSS-HIERARCHY ATTENTION
Chengze Wang, Zhiyu Jiang, Yuan Yuan, School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, China
TU2.R18.9: A FINE-GRAINED SHIP DETECTION FRAMEWORK BASED ON FIXED ROI MASKING AND FEATURE OPTIMIZATION IN OPTICAL REMOTE SENSING IMAGES
Xiaohan Zhang, Libo Yao, Yafei Lv, Mengyang Li, Xun Lin, Naval Aviation University, China
TU2.R18.10: INSTANCE SEGMENTATION WITH ORIENTED PROPOSALS FOR AERIAL IMAGES
Ting Pan, Jian Ding, Jinwang Wang, Wen Yang, Gui-Song Xia, Wuhan University, China
TU2.R18.11: SEMI-AUTOMATIC CLASSIFICATION OF BUILDING FROM LOW-DENSITY LIDAR DATA AND WORLDVIEW-2 IMAGES THROUGH OBIA TECHNIQUE
Chiara Zarro, Silvia Liberata Ullo, University of Sannio, Italy; Giuseppe Meoli, Mariano Focareta, Mapsat, Italy