Datasets › Dayton
Dayton
The Dayton dataset is a dataset for ground-to-aerial (or aerial-to-ground) image translation, or cross-view image synthesis. It contains images of road views and aerial views of roads. There are 76,048 images in total and the train/test split is 55,000/21,048. The images in the original dataset have 354×354 resolution.
Source: Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation Image Source: https://arxiv.org/abs/1912.06112
Benchmarks archive 2025-07-28
All 4 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Cross-View Image-to-Image Translation | Dayton (256×256) - aerial-to-ground | SelectionGAN SSIM 0.5938 | Multi-Channel Attention Selection GAN with Cascaded... | Ha0Tang/SelectionGAN +2 | 6 | Compare |
| Cross-View Image-to-Image Translation | Dayton (64×64) - aerial-to-ground | SelectionGAN SSIM 0.6865 | Multi-Channel Attention Selection GAN with Cascaded... | Ha0Tang/SelectionGAN +2 | 5 | Compare |
| Cross-View Image-to-Image Translation | Dayton (64x64) - ground-to-aerial | SelectionGAN SSIM 0.5118 | Multi-Channel Attention Selection GAN with Cascaded... | Ha0Tang/SelectionGAN +2 | 5 | Compare |
| Cross-View Image-to-Image Translation | Dayton (256×256) - ground-to-aerial | SelectionGAN SSIM 0.3284 | Multi-Channel Attention Selection GAN with Cascaded... | Ha0Tang/SelectionGAN +2 | 4 | Compare |
Papers archive 2025-07-28
6 shown of 6 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 13. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation | 2 | 1 | 27 Dec 2019 | not harvested |
| Unified Generative Adversarial Networks for Controllable Image-to-Image Translation | 1 | 3 | 12 Dec 2019 | not harvested |
| Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation | 3 | 4 | 15 Apr 2019 | not harvested |
| Cross-view image synthesis using geometry-guided conditional GANs | 2 | 1 | 14 Aug 2018 | not harvested |
| Cross-View Image Synthesis using Conditional GANs | 1 | 7 | 9 Mar 2018 | not harvested |
| Image-to-Image Translation with Conditional Adversarial Networks | 192 | 4 | 21 Nov 2016 | ran 14 of 122 samples (108 unverified; 1 pointer-only for licence) |
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Dayton (64×64) - aerial-to-ground
- Dayton (64x64) - ground-to-aerial
- Dayton (256×256) - aerial-to-ground
- Dayton (256×256) - ground-to-aerial
- Dayton
5 variant names, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections