Datasets › DroneDeploy
DroneDeploy
From DroneDeploy:
We’ve collected a dataset of aerial orthomosaics and elevation images. These have been annotated into 6 different classes: Ground, Water, Vegetation, Cars, Clutter, and Buildings. The resolution of the images is approximately 10cm per pixel which gives them a great level of detail. We’re looking forward to making more data available and encourage more research into the impact this imagery can have in furthering safety, conservation, and efficiency.
Image source: https://arxiv.org/pdf/2012.02024v1.pdf
Source: DroneDeploy Segmentation Benchmark Challenge Image Source: title
Benchmarks archive 2025-07-28
All 1 leaderboard 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 | ||||
|---|---|---|---|---|---|---|
| Semantic Segmentation | DroneDeploy | DLv3+ (Xception65) Mean IoU (test) 52.5 | Aerial Imagery Pixel-level Segmentation | mrheffels/aerial-imagery-segmentation | 1 | Compare |
Papers archive 2025-07-28
1 shown of 1 paper 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 1. 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 | |||
|---|---|---|---|---|
| Aerial Imagery Pixel-level Segmentation | 1 | 1 | 3 Dec 2020 | not harvested |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Unknown
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- DroneDeploy
1 variant name, as the archive lists them.
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