Generating Synthetic Satellite Imagery With Deep-Learning Text-to-Image Models -- Technical Challenges and Implications for Monitoring and Verification

arXiv:2404.07754v1 Announce Type: cross
Abstract: 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. These technologies have already been used to generate training data for Machine Learning (ML) models, and large text-to-image models like DALL-E 2, Imagen, and Stable Diffusion are achieving remarkable results in realistic high-resolution image generation. Given these developments, issues of data authentication in monitoring and verification deserve a careful and …

abstract architectures arxiv challenges cs.ai cs.cv cs.hc cs.lg data digital digital media generate image images machine machine learning media monitoring novel photorealistic photorealistic images real data satellite synthetic technical technologies text text-to-image training training data type verification