تقرير
Part-aware Panoptic Segmentation
| العنوان: | Part-aware Panoptic Segmentation |
|---|---|
| المؤلفون: | de Geus, Daan, Meletis, Panagiotis, Lu, Chenyang, Wen, Xiaoxiao, Dubbelman, Gijs |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | 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. Comment: CVPR 2021. Code and data: https://github.com/tue-mps/panoptic_parts |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2106.06351 |
| رقم الأكسشن: | edsarx.2106.06351 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |