2020
Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks
CVPR 2020poster
Building a large image dataset with high-quality object masks for semantic segmentation is costly and time-consuming. In this paper, we introduce a principled semi-supervised framework that only use a small set of fully supervised images (having semantic segmentation labels and box labels) and a set…