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@@ -24,13 +24,6 @@ It aggregates the images and metadata from Cityscapes[^1], Cityscapes-VPS[^2] an
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  This comprehensive derivative was created out of the need for a batteries-included variant of the dataset for academic purposes.
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  Specifically, joining samples from the individual datasets in their original structure (each is organized differently) involves a significant amount of boilerplate code.
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- [^1]: `Cordts et al., “The Cityscapes Dataset for Semantic Urban Scene Understanding” (CVPR 2016)`
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- [^2]: `Kim et al., "Video Panoptic Segmentation" (CVPR 2020)`
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- [^3]: `Qiao et al., "Learning Visual Perception with Depth-aware Video Panoptic Segmentation" (CVPR 2021)`
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  This dataset is relevant to computer vision research areas such as:
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  - Segmentation
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  [Cityscapes-DVPS](https://github.com/joe-siyuan-qiao/ViP-DeepLab) datasets.
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  This comprehensive derivative was created out of the need for a batteries-included variant of the dataset for academic purposes.
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  Specifically, joining samples from the individual datasets in their original structure (each is organized differently) involves a significant amount of boilerplate code.
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  This dataset is relevant to computer vision research areas such as:
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  - Segmentation
 
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  [Cityscapes-DVPS](https://github.com/joe-siyuan-qiao/ViP-DeepLab) datasets.
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+ [^1]: Cordts et al., “The Cityscapes Dataset for Semantic Urban Scene Understanding” (CVPR 2016)
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+ [^2]: Kim et al., "Video Panoptic Segmentation" (CVPR 2020)
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+ [^3]: Qiao et al., "Learning Visual Perception with Depth-aware Video Panoptic Segmentation" (CVPR 2021)
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