mlsanityData to 7 Oct 2026

Mask Conditional Synthetic Satellite Imagery

arXiv 2302.04305 ↗First posted 8 Feb 2023cs.CV cs.LGcited by 4

Not on the map. Why?

Abstract (arXiv)

In this paper we propose a mask-conditional synthetic image generation model for creating synthetic satellite imagery datasets. Given a dataset of real high-resolution images and accompanying land cover masks, we show that it is possible to train an upstream conditional synthetic imagery generator, use that generator to create synthetic imagery with the land cover masks, then train a downstream model on the synthetic imagery and land cover masks that achieves similar test performance to a model that was trained with the real imagery. Further, we find that incorporating a mixture of real and synthetic imagery acts as a data augmentation method, producing better models than using only real imagery (0.5834 vs. 0.5235 mIoU). Finally, we find that encouraging diversity of outputs in the upstream model is a necessary component for improved downstream task performance. We have released code for reproducing our work on GitHub, see https://github.com/ms-synthetic-satellite-image/synthetic-satellite-imagery .

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 17 of its 25 references that are in the map. First posted on arXiv 8 Feb 2023.

Builds on

17 of 25 references.

References · 17

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2022Generative Adversarial Networkscited by 5,603
  4. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  5. 2013Auto-Encoding Variational Bayescited by 3,980
  6. 2014Conditional Generative Adversarial Netscited by 2,152
  7. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,295
  8. 2016Conditional Image Synthesis With Auxiliary Classifier GANscited by 562
  9. 2019SEAN: Image Synthesis with Semantic Region-Adaptive Normalizationcited by 253
  10. 2018Synthetic Data Augmentation using GAN for Improved Liver Lesion Classificationcited by 136
  11. 2019Meta-Sim: Learning to Generate Synthetic Datasetscited by 128
  12. 2016Understanding data augmentation for classification: when to warp?cited by 74
5 more
  1. 2019PPGAN: Privacy-preserving Generative Adversarial Networkcited by 34
  2. 2019ColorMapGAN: Unsupervised Domain Adaptation for Semantic Segmentation Using Color Mapping Generative Adversarial Networkscited by 26
  3. 2022Fast building segmentation from satellite imagery and few local labelscited by 9
  4. 2020Deep Snow: Synthesizing Remote Sensing Imagery with Generative Adversarial Netscited by 5
  5. 2022Conditional Progressive Generative Adversarial Network for satellite image generationcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 1.

4 papers.

  1. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagerycited by 130
  2. 2023Generate Your Own Scotland: Satellite Image Generation Conditioned on Mapscited by 30
  3. 2024Deep Learning for Slum Mapping in Remote Sensing Images: A Meta-analysis and Reviewcited by 1
  4. 2026Synthetic Data Augmentation for Satellite-Based Analysis of Battle-Damaged Agricultural Fields in Ukrainecited by 0