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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 6170 of 296 papers

TitleStatusHype
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance SegmentationCode1
An Alternative to WSSS? An Empirical Study of the Segment Anything Model (SAM) on Weakly-Supervised Semantic Segmentation ProblemsCode1
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic SegmentationCode1
ISIM: Iterative Self-Improved Model for Weakly Supervised SegmentationCode1
L2G: A Simple Local-to-Global Knowledge Transfer Framework for Weakly Supervised Semantic SegmentationCode1
Discriminative Region Suppression for Weakly-Supervised Semantic SegmentationCode1
Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic SegmentationCode1
DHR: Dual Features-Driven Hierarchical Rebalancing in Inter- and Intra-Class Regions for Weakly-Supervised Semantic SegmentationCode1
Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic SegmentationCode1
Masked Based Unsupervised Content TransferCode1
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