Guide to Panoptic Segmentation - A Semantic + Instance Segmentation Approach

Panoptic segmentation is an image segmentation method used for Computer Vision tasks. It unifies two distinct concepts used to segment images namely, semantic segmentation and instance segmentation. Panoptic segmentation technique was introduced by Kaiming He, Ross Girshick and Piotr Dollar of Facebook AI Research (FAIR), Carsten Rother of HCI/IWR, Heidelberg University (Germany) as well as Alexander Kirillov, a member of both the above mentioned organizations in April 2019 (version v3). Let us first understand semantic segmentation and instance segmentation approaches in order to have clarity about panoptic segmentation. A Computer Vision project aims at developing a deep learning model which can accurately and precisely detect real-world objects comprising the input data in the form of images or videos.