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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 141–150 of 296 papers

TitleStatusHype
DIAL: Dense Image-text ALignment for Weakly Supervised Semantic Segmentation—0
Dual-Augmented Transformer Network for Weakly Supervised Semantic Segmentation—0
Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation—0
ECS-Net: Improving Weakly Supervised Semantic Segmentation by Using Connections Between Class Activation Maps—0
Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation—0
Enhancing Weakly Supervised Semantic Segmentation with Multi-modal Foundation Models: An End-to-End Approach—0
Enhancing Weakly Supervised Semantic Segmentation for Fibrosis via Controllable Image Generation—0
Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation—0
Exploiting Shape Cues for Weakly Supervised Semantic Segmentation—0
Exploring Pixel-level Self-supervision for Weakly Supervised Semantic Segmentation—0
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