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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 201–210 of 296 papers

TitleStatusHype
Weakly-Supervised Semantic Segmentation using Motion Cues—0
Weakly Supervised Semantic Segmentation using Web-Crawled Videos—0
Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise—0
3D Guided Weakly Supervised Semantic Segmentation—0
Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets—0
Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching—0
ECS-Net: Improving Weakly Supervised Semantic Segmentation by Using Connections Between Class Activation Maps—0
Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation—0
Segment Anything is A Good Pseudo-label Generator for Weakly Supervised Semantic Segmentation—0
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