Papers › Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene Understanding

Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene Understanding

16 Apr 2020arXiv:2004.07944archive 2025-07-28

Panagiotis Meletis, Xiaoxiao Wen, Chenyang Lu, Daan de Geus, Gijs Dubbelman

In this technical report, we present two novel datasets for image scene understanding. Both datasets have annotations compatible with panoptic segmentation and additionally they have part-level labels for selected semantic classes. This report describes the format of the two datasets, the annotation protocols, the merging strategies, and presents the datasets statistics. The datasets labels together with code for processing and visualization will be published at https://github.com/tue-mps/panoptic_parts.

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tue-mps/panoptic_parts officialmentioned in papermentioned on GitHubtfApache-2.0 report
chufengt/ViRReq mentioned on GitHubpytorchApache-2.0 report
chufengt/Visual-Recognition-by-Request mentioned on GitHubpytorchApache-2.0 report
pmeletis/panoptic_parts mentioned on GitHubpytorch report

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filepaths_pairs_fn_OLD pmeletis/panoptic_parts/panoptic_parts/evaluation/eval_PartPQ.py community (archive-listed) ran · our draft was wrong Apache-2.0 (permissive) · c6704fa8b1518821 · report
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Tasks

Human Part SegmentationPanoptic SegmentationPart-aware Panoptic SegmentationScene UnderstandingSemantic ParsingSemantic Segmentation

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