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--- |
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license: mit |
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task_categories: |
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- depth-estimation |
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- keypoint-detection |
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- image-feature-extraction |
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pretty_name: AerialExtreMatch Benchmark |
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viewer: false |
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tags: |
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- image |
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--- |
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# AerialExtreMatch — Benchmark Dataset |
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[Code](https://github.com/Xecades/AerialExtreMatch) | [Project Page](https://xecades.github.io/AerialExtreMatch/) | Paper (WIP) |
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This repo contains the **benchmark** set for our paper *AerialExtreMatch: A Benchmark for Extreme-View Image Matching and Localization*. 32 difficulty levels are included. We also provide [**train**](https://huggingface.co/datasets/Xecades/AerialExtreMatch-Train) and [**localization**](https://huggingface.co/datasets/Xecades/AerialExtreMatch-Localization) datasets. |
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## Usage |
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Simply clone this repository and unzip the dataset files. |
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```bash |
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git clone git@hf.co:datasets/Xecades/AerialExtreMatch-Benchmark |
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cd AerialExtreMatch-Benchmark |
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unzip "*.zip" |
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rm -rf *.zip |
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rm -rf .git |
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``` |
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## Dataset Structure |
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After unpacking each .zip file: |
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<pre> |
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. |
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└── class_[id] <i>(class_0~class_31)</i> |
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├── class_[id].npy |
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├── depth: *.exr |
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└── rgb: *.jpg |
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</pre> |
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- Keys of `class_[id].npy` files: `['poses', 'intrinsics', 'depth', 'rgb', 'overlap', 'pitch', 'scale', 'pair']`. |
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## Classification Metric |
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Note that the actual folders are 0-indexed, but the table below is 1-indexed for consistency with the paper, i.e. level 5 corresponds to `class_4`. |
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