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Part-aware Panoptic Segmentation

2021-06-11 · CVPR 2021 1 · Daan de Geus, Panagiotis Meletis, Chenyang Lu, Xiaoxiao Wen, Gijs Dubbelman

In this work, we introduce the new scene understanding task of Part-aware Panoptic Segmentation (PPS), which aims to understand a scene at multiple levels of abstraction, and unifies the tasks of scene parsing and part parsing. For this novel task, we provide consistent annotations on two commonly used datasets: Cityscapes and Pascal VOC. Moreover, we present a single metric to evaluate PPS, called Part-aware Panoptic Quality (PartPQ). For this new task, using the metric and annotations, we set multiple baselines by merging results of existing state-of-the-art methods for panoptic segmentation and part segmentation. Finally, we conduct several experiments that evaluate the importance of the different levels of abstraction in this single task.

📄 PDF Abstract BibTeX arXiv:2106.06351

Code (1)

tue-mps/panoptic_parts 공식 구현 tf

Tasks

Image SegmentationPanoptic SegmentationPart-aware Panoptic SegmentationScene ParsingScene UnderstandingSegmentation

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