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Weakly-Supervised Semantic Segmentation

The semantic segmentation task is to assign a label from a label set to each pixel in an image. In the case of fully supervised setting, the dataset consists of images and their corresponding pixel-level class-specific annotations (expensive pixel-level annotations). However, in the weakly-supervised setting, the dataset consists of images and corresponding annotations that are relatively easy to obtain, such as tags/labels of objects present in the image.

( Image credit: Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing )

Papers

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Showing 121–130 of 296 papers

TitleStatusHype
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation—0
Background Noise Reduction of Attention Map for Weakly Supervised Semantic Segmentation—0
COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation—0
HistoSegCap: Capsules for Weakly-Supervised Semantic Segmentation of Histological Tissue Type in Whole Slide Images—0
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
CoBra: Complementary Branch Fusing Class and Semantic Knowledge for Robust Weakly Supervised Semantic Segmentation—0
Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation—0
Gated CRF Loss for Weakly Supervised Semantic Image Segmentation—0
3D Guided Weakly Supervised Semantic Segmentation—0
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