3 papers
cs.CV2024
Generating Synthetic Satellite Imagery for Rare Objects: An Empirical Comparison of Models and Metrics
Tuong Vy Nguyen, Johannes Hoster, Alexander Glaser +2
Generative deep learning architectures can produce realistic, high-resolution fake imagery -- with potentially drastic societal implications. A key question in this context is: How…
cs.CV2024
Using Game Engines and Machine Learning to Create Synthetic Satellite Imagery for a Tabletop Verification Exercise
Johannes Hoster, Sara Al-Sayed, Felix Biessmann +4
Satellite imagery is regarded as a great opportunity for citizen-based monitoring of activities of interest. Relevant imagery may however not be available at sufficiently high reso…
cs.CV2024
Generating Synthetic Satellite Imagery With Deep-Learning Text-to-Image Models -- Technical Challenges and Implications for Monitoring and Verification
Tuong Vy Nguyen, Alexander Glaser, Felix Biessmann
Novel deep-learning (DL) architectures have reached a level where they can generate digital media, including photorealistic images, that are difficult to distinguish from real data…