MOP1.PD.4
A MULTI-VIEW APPROACH FOR PHYSICALLY-GUIDED SAR IMAGE GENERATION BASED ON STYLEGAN2
Ran Yang, Tao Lai, Haifeng Huang, Sun Yat-sen University, China
Session:
MOP1.PD: Physics Aware AI Models for SAR Data Generation and Understanding: Towards Global Environmental Monitoring I Poster
Track:
Community-Contributed Sessions
Location:
Plaza Ballroom: Poster Area D
Presentation Time:
Monday, 4 August, 14:30 - 15:45
Session Co-Chairs:
Zhongling Huang, Northwestern Polytechnical University and Mihai Datcu, Politehnica University of Bucharest
Session MOP1.PD
MOP1.PD.1: Dynamic Information Dense Conditional Generation Network for SAR Moving Target Segmentation
Yifan Wu, Lijia Huang, Siyang You, Bingchen Zhang, Aerospace Information Research Institute, Chinese Academy of Sciences, China
MOP1.PD.2: Physical authenticity evaluation of SAR image via scattering center feature matching
Yihan Zhuang, Zhongling Huang, Northwestern Polytechnical University, China
MOP1.PD.3: Point2Ship: Leveraging Prior SAR Ship Knowledge for End-to-End Ship Detection with Point Supervision
Qiwei Ma, Puhong Duan, Xukun Lu, Xudong Kang, Shutao Li, Hunan University, China
MOP1.PD.4: A MULTI-VIEW APPROACH FOR PHYSICALLY-GUIDED SAR IMAGE GENERATION BASED ON STYLEGAN2
Ran Yang, Tao Lai, Haifeng Huang, Sun Yat-sen University, China
MOP1.PD.5: A Segmentation Method for Ship and Chaff in Overlapping Scenarios of SAR Images Based on polarimetric Information
Yimin Yang, Ping Lang, Chong Wang, Yingzhu Zhao, Tsinghua University, China; Yanlei Du, Jian Yang, Chinese Academy of Sciences, China
MOP1.PD.6: Geometry Reconstruction of Few Views SAR Images Based on Differentiable Ray Tracing
Jiangtao Wei, Feng Xu, Fudan University, China
Resources