OneFormer: One Transformer to Rule Universal Image Segmentation

Abstract

Universal Image Segmentation is not a new concept. Past attempts to unify image segmentation in the last decades include scene parsing, panoptic segmentation, and, more recently, new panoptic architectures. We propose OneFormer, a universal image segmentation framework that unifies segmentation with a multi-task train-once design.

Publication
IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023