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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

Showing 131140 of 296 papers

TitleStatusHype
Fully Convolutional Multi-Class Multiple Instance LearningCode0
Removing supervision in semantic segmentation with local-global matching and area balancingCode0
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion ModelsCode0
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image DomainsCode0
Fine-grained Background Representation for Weakly Supervised Semantic SegmentationCode0
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation ApproachCode0
CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic SegmentationCode0
FFR: Frequency Feature Rectification for Weakly Supervised Semantic SegmentationCode0
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