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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 261270 of 296 papers

TitleStatusHype
Leveraging Swin Transformer for Local-to-Global Weakly Supervised Semantic SegmentationCode0
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic SegmentationCode0
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation ApproachCode0
Removing supervision in semantic segmentation with local-global matching and area balancingCode0
C-CAM: Causal CAM for Weakly Supervised Semantic Segmentation on Medical ImageCode0
Rethinking Saliency-Guided Weakly-Supervised Semantic SegmentationCode0
Learning Pseudo Labels for Semi-and-Weakly Supervised Semantic SegmentationCode0
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic SegmentationCode0
Joint Learning of Saliency Detection and Weakly Supervised Semantic SegmentationCode0
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