Datasets:
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README.md
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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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