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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 91100 of 296 papers

TitleStatusHype
Hierarchical Semantic Contrast for Weakly Supervised Semantic SegmentationCode1
RecurSeed and EdgePredictMix: Pseudo-Label Refinement Learning for Weakly Supervised Semantic Segmentation across Single- and Multi-Stage FrameworksCode1
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event CamerasCode1
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic SegmentationCode1
Class Re-Activation Maps for Weakly-Supervised Semantic SegmentationCode1
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic SegmentationCode1
Class Tokens Infusion for Weakly Supervised Semantic SegmentationCode1
Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic SegmentationCode1
Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional NetworksCode1
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