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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 111–120 of 296 papers

TitleStatusHype
Hierarchical Semantic Contrast for Weakly Supervised Semantic SegmentationCode1
Background Noise Reduction of Attention Map for Weakly Supervised Semantic Segmentation—0
Image Augmentation Agent for Weakly Supervised Semantic Segmentation—0
A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation—0
Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image—0
Hypergraph Convolutional Networks 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
LID 2020: The Learning from Imperfect Data Challenge Results—0
Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation—0
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