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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 181–190 of 296 papers

TitleStatusHype
Weakly-Supervised Semantic Segmentation of Ships Using Thermal Imagery—0
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation—0
Attention-based Class Activation Diffusion for Weakly-Supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation of Echocardiography Videos via Multi-level Features Selection—0
SLAMs: Semantic Learning based Activation Map for Weakly Supervised Semantic Segmentation—0
Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation—0
WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain LabelsCode0
Weakly Supervised Semantic Segmentation via Progressive Patch LearningCode0
Exploiting Shape Cues for Weakly Supervised Semantic Segmentation—0
Learning Pseudo Labels for Semi-and-Weakly Supervised Semantic SegmentationCode0
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