TH2.R3.3
SynGlSat: Geographically Equitable Synthesis of Global Satellite Imagery
Umur Ciftci, Liam Melchior, Binghamton University, United States; Ilke Demir, Cauth AI, United States
Session:
TH2.R3: Synthetic Remote Sensing Image Synthesis, Quality and Deepfake Detection Oral
Track:
Community Contributed Themes
Location:
TBD
Presentation Time:
Thu, 13 Aug, 11:30 - 11:45
Session Co-Chairs:
Jacob Arndt, Oak Ridge National Laboratory and Ilke Demir, Cauth AI
Presentation
Discussion
Resources
No resources available.
Session TH2.R3
TH2.R3.1: TOWARDS A SATELLITE IMAGE MANIPULATION AND DEEPFAKE LOCALIZATION BENCHMARK DATASET
Jacob Arndt, Debvrat Varshney, Philipe Dias, Nivedita Nukavarapu, Oak Ridge National Laboratory, United States
TH2.R3.2: TOWARD EFFICIENT, EXPLAINABLE SATELLITE DEEPFAKE DETECTION: COLOUR AND FREQUENCY BAND CONTRIBUTIONS
Virginia Ziulu, James Garforth, University of Edinburgh, United Kingdom
TH2.R3.3: SynGlSat: Geographically Equitable Synthesis of Global Satellite Imagery
Umur Ciftci, Liam Melchior, Binghamton University, United States; Ilke Demir, Cauth AI, United States
TH2.R3.4: EVALUATING MULTIMODAL SATELLITE IMAGE-METADATA CONTRASTIVE LEARNING
Nivedita Nukavarapu, Philipe Ambrozio Dias, Debvrat Varshney, Jacob Arndt, Oak Ridge National Laboratory, United States
TH2.R3.5: SO(2)-AWARE PIXEL-SPACE CONDITIONAL DIFFUSION TRANSFORMER FOR MULTI-ANGLE SAR TARGET IMAGE GENERATION
Ran Yang, Tao Lai, Haifeng Huang, Sun Yat-sen University, China
Contacts