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SegFly

Tasks:
Image Segmentation
Modalities:
Image
Text
Geospatial
Formats:
parquet
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
segmentation
semantic-segmentation
multimodal
aerial
drone
uav
Libraries:
Datasets
Dask
Polars
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.tgz filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ *.sam filter=lfs diff=lfs merge=lfs -text
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+ *.raw filter=lfs diff=lfs merge=lfs -text
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+ *.ogg filter=lfs diff=lfs merge=lfs -text
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+ *.wav filter=lfs diff=lfs merge=lfs -text
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+ # Image files - uncompressed
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+ *.png filter=lfs diff=lfs merge=lfs -text
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+ *.tiff filter=lfs diff=lfs merge=lfs -text
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+ # Image files - compressed
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+ ---
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+ pretty_name: "SegFly: A Dataset and 2D-3D-2D Paradigm for Aerial RGB-Thermal Semantic Segmentation at Scale"
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+ task_categories:
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+ - image-segmentation
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+ task_ids:
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+ - semantic-segmentation
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+ license: cc-by-nc-sa-4.0
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+ language:
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+ - en
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+ size_categories:
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+ - 10K<n<100K
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+ tags:
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+ - segmentation
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+ - semantic-segmentation
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+ - multimodal
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+ - aerial
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+ - drone
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+ - uav
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+ - remote-sensing
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+ - rgb-thermal
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+ - thermal
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+ ---
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+
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+ <div align="center">
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+
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+ # SegFly: A Dataset and 2D-3D-2D Paradigm for Aerial RGB-Thermal Semantic Segmentation at Scale
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+
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+
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+ [![GitHub Documentation](https://img.shields.io/badge/GitHub-Documentation-green?logo=github&logoColor=white&labelColor=555)](https://github.com/markus-42/SegFly)&nbsp;&nbsp;
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+ [![Project](https://img.shields.io/badge/Project-Page-blue.svg)](https://markus-42.github.io/publications/2026/segfly/)&nbsp;&nbsp;
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+ [![arXiv](https://img.shields.io/badge/arXiv-Paper-red.svg)](https://arxiv.org/abs/2603.17920)&nbsp;&nbsp;
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+ [![Firefly Model](https://img.shields.io/badge/HuggingFace-Firefly%20Model%20-e58f00?logo=huggingface&logoColor=white&labelColor=555)](https://huggingface.co/markus-42/SegFly-Firefly)
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+
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+
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+
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+ </div>
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+
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+ Following the acceptance of [SegFly](https://markus-42.github.io/publications/2026/segfly/) at the ECCV 2026 computer vision conference, we officially release our dataset on Hugging Face. Note that we also release our [Firefly](https://huggingface.co/markus-42/SegFly-Firefly) model, specialized for RGB and thermal semantic segmentation from aerial perspectives.
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+
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+ SegFly is a large-scale aerial semantic segmentation dataset featuring 20,606 high-resolution RGB images and 15,007 pixel-aligned RGB-Thermal (RGB-T) pairs. Images are captured across urban, industrial, and rural environments, spanning all seasons and three altitudes (30m, 40m, 50m).
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+
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+
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+
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+ ## Quickstart
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+
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+ > **Full dataset documentation available on [SegFly GitHub](https://github.com/markus-42/SegFly).**
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load entire dataset
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+ dataset = load_dataset("markus-42/SegFly")
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+ ```
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+
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+ ## Features
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+
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+ | Feature | Type | Description |
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+ | :--- | :---: | :--- |
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+ | `image` | `Image` | Raw sensor frame (RGB or LWIR Thermal) |
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+ | `label` | `Image` | 8-bit single-channel semantic mask mapped to 15 benchmark classes |
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+ | `RGB_aligned` | `Image` | Registered RGB image (Thermal modality only; returns `None` for RGB modality) |
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+ | `scene` | `string` | Scene identifier (`"scene_01"` to `"scene_09"`) |
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+ | `altitude` | `string` | Flight altitude (`"30m"`, `"40m"`, `"50m"`) |
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+ | `modality` | `string` | Sensor modality (`"RGB"` or `"thermal"`) |
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+
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+ ## Splits and Statistics
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+
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+ * **Total Samples**: 35,613 (20,606 RGB + 15,007 thermal)
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+
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+ | Modality | Split | Scenes | Sample Count |
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+ | :--- | :--- | :--- | :---: |
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+ | **RGB** | Train | `scene_01`, `scene_02`, `scene_03`, `scene_04`, `scene_05` | 14,738 |
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+ | | Val | `scene_06`, `scene_07` | 1,965 |
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+ | | Test | `scene_08`, `scene_09` | 3,842 |
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+ | **Thermal** | Train | `scene_03`, `scene_04`, `scene_05` | 12,063 |
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+ | | Val/Test | `scene_09` | 2,944 |
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+
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+ ## SegFly Dataset Class Mapping Reference
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+
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+ | Class ID | Class Name | RGB Color | Color Preview |
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+ | :---: | :--- | :---: | :---: |
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+ | 0 | Unlabeled / Ignored | `[0, 0, 0]` | <span style="display:inline-block; width:12px; height:12px; background-color:#000000; border:1px solid #000; margin-right:5px;"></span>`#000000` |
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+ | 1 | Road | `[128, 0, 128]` | <span style="display:inline-block; width:12px; height:12px; background-color:#800080; border:1px solid #000; margin-right:5px;"></span>`#800080` |
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+ | 2 | Walkway | `[204, 163, 72]` | <span style="display:inline-block; width:12px; height:12px; background-color:#cca348; border:1px solid #000; margin-right:5px;"></span>`#cca348` |
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+ | 3 | Dirt | `[128, 0, 0]` | <span style="display:inline-block; width:12px; height:12px; background-color:#800000; border:1px solid #000; margin-right:5px;"></span>`#800000` |
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+ | 4 | Gravel | `[192, 192, 192]` | <span style="display:inline-block; width:12px; height:12px; background-color:#c0c0c0; border:1px solid #000; margin-right:5px;"></span>`#c0c0c0` |
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+ | 6 | Grass | `[0, 255, 0]` | <span style="display:inline-block; width:12px; height:12px; background-color:#00ff00; border:1px solid #000; margin-right:5px;"></span>`#00ff00` |
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+ | 7 | Vegetation | `[112, 148, 32]` | <span style="display:inline-block; width:12px; height:12px; background-color:#709420; border:1px solid #000; margin-right:5px;"></span>`#709420` |
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+ | 8 | Tree | `[64, 64, 0]` | <span style="display:inline-block; width:12px; height:12px; background-color:#404000; border:1px solid #000; margin-right:5px;"></span>`#404000` |
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+ | 9 | Ground Obstacle | `[255, 255, 0]` | <span style="display:inline-block; width:12px; height:12px; background-color:#ffff00; border:1px solid #000; margin-right:5px;"></span>`#ffff00` |
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+ | 13 | Vehicle | `[0, 128, 128]` | <span style="display:inline-block; width:12px; height:12px; background-color:#008080; border:1px solid #000; margin-right:5px;"></span>`#008080` |
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+ | 14 | Water | `[0, 0, 255]` | <span style="display:inline-block; width:12px; height:12px; background-color:#0000ff; border:1px solid #000; margin-right:5px;"></span>`#0000ff` |
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+ | 16 | Building | `[255, 0, 0]` | <span style="display:inline-block; width:12px; height:12px; background-color:#ff0000; border:1px solid #000; margin-right:5px;"></span>`#ff0000` |
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+ | 17 | Roof | `[64, 160, 120]` | <span style="display:inline-block; width:12px; height:12px; background-color:#40a078; border:1px solid #000; margin-right:5px;"></span>`#40a078` |
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+ | 33 | Parking Lot | `[128, 64, 128]` | <span style="display:inline-block; width:12px; height:12px; background-color:#804080; border:1px solid #000; margin-right:5px;"></span>`#804080` |
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+ | 34 | Construction | `[240, 120, 120]` | <span style="display:inline-block; width:12px; height:12px; background-color:#f07878; border:1px solid #000; margin-right:5px;"></span>`#f07878` |
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+ | 36 | Truck | `[128, 128, 64]` | <span style="display:inline-block; width:12px; height:12px; background-color:#808040; border:1px solid #000; margin-right:5px;"></span>`#808040` |
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+
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+
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+ ## Reference
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+
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+ ```bibtex
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+ @inproceedings{gross2026segfly,
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+ title={{SegFly: A Dataset and 2D-3D-2D Paradigm for Aerial RGB-Thermal Semantic Segmentation at Scale}},
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+ author={Markus Gross and Sai Bharadhwaj Matha and Rui Song and Viswanathan Muthuveerappan and Conrad Christoph and Julius Huber and Daniel Cremers},
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+ booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
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+ year={2026},
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+ }
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+ ```
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+
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+ ## License
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+ This work is licensed under the [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/). See the LICENSE file for the full legal terms.
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+
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+
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