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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 231240 of 296 papers

TitleStatusHype
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic SegmentationCode1
Realizing Pixel-Level Semantic Learning in Complex Driving Scenes based on Only One Annotated Pixel per Class0
Weakly Supervised Semantic Segmentation of Satellite Images for Land Cover Mapping -- Challenges and OpportunitiesCode1
Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning0
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image DomainsCode0
Neural Diffusion Distance for Image Segmentation0
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation ApproachCode0
Self-Supervised Difference Detection for Weakly-Supervised Semantic SegmentationCode0
Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic SegmentationCode0
HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide ImagesCode0
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