Part-aware Panoptic Segmentation (2106.06351v1)
Abstract: 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.
- Daan de Geus (21 papers)
- Panagiotis Meletis (13 papers)
- Chenyang Lu (34 papers)
- Xiaoxiao Wen (3 papers)
- Gijs Dubbelman (34 papers)