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Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
[article]
2015
arXiv
pre-print
We propose a novel deep neural network architecture for semi-supervised semantic segmentation using heterogeneous annotations. Contrary to existing approaches posing semantic segmentation as a single task of region-based classification, our algorithm decouples classification and segmentation, and learns a separate network for each task. In this architecture, labels associated with an image are identified by classification network, and binary segmentation is subsequently performed for each
arXiv:1506.04924v2
fatcat:kdljwoets5h53jes3iwph75ypy