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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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- > WARNING: working in progress.
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-
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  ## Usage
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  Simply clone this repository and unzip the dataset files.
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  rm -rf .git
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  ```
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- TODO: provide a python example.
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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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  - Keys of `class_[id].npy` files: `['poses', 'intrinsics', 'depth', 'rgb', 'overlap', 'pitch', 'scale', 'pair']`.
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- - Refer to original paper for details on classification.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  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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  - Keys of `class_[id].npy` files: `['poses', 'intrinsics', 'depth', 'rgb', 'overlap', 'pitch', 'scale', 'pair']`.
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+ ## Classification Metric
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+
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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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+
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+ <!-- TODO: replace with paper table -->
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+ | Level | Overlap | Pitch | Scale |
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+ | ----- | ------- | ----- | ------- |
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+ | 1 | 60+ | 55-60 | 1.0-2.0 |
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+ | 2 | 60+ | 60-65 | 1.0-2.0 |
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+ | 3 | 60+ | 65-70 | 1.0-2.0 |
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+ | 4 | 60+ | 70-75 | 1.0-2.0 |
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+ | 5 | 40-60 | 55-60 | 1.0-2.0 |
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+ | 6 | 40-60 | 60-65 | 1.0-2.0 |
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+ | 7 | 40-60 | 65-70 | 1.0-2.0 |
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+ | 8 | 40-60 | 70-75 | 1.0-2.0 |
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+ | 9 | 20-40 | 55-60 | 1.0-2.0 |
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+ | 10 | 20-40 | 60-65 | 1.0-2.0 |
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+ | 11 | 20-40 | 65-70 | 1.0-2.0 |
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+ | 12 | 20-40 | 70-75 | 1.0-2.0 |
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+ | 13 | 20- | 55-60 | 1.0-2.0 |
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+ | 14 | 20- | 60-65 | 1.0-2.0 |
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+ | 15 | 20- | 65-70 | 1.0-2.0 |
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+ | 16 | 20- | 70-75 | 1.0-2.0 |
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+ | 17 | 60+ | 55-60 | 2.0+ |
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+ | 18 | 60+ | 60-65 | 2.0+ |
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+ | 19 | 60+ | 65-70 | 2.0+ |
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+ | 20 | 60+ | 70-75 | 2.0+ |
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+ | 21 | 40-60 | 55-60 | 2.0+ |
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+ | 22 | 40-60 | 60-65 | 2.0+ |
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+ | 23 | 40-60 | 65-70 | 2.0+ |
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+ | 24 | 40-60 | 70-75 | 2.0+ |
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+ | 25 | 20-40 | 55-60 | 2.0+ |
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+ | 26 | 20-40 | 60-65 | 2.0+ |
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+ | 27 | 20-40 | 65-70 | 2.0+ |
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+ | 28 | 20-40 | 70-75 | 2.0+ |
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+ | 29 | 20- | 55-60 | 2.0+ |
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+ | 30 | 20- | 60-65 | 2.0+ |
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+ | 31 | 20- | 65-70 | 2.0+ |
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+ | 32 | 20- | 70-75 | 2.0+ |