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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 5160 of 296 papers

TitleStatusHype
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
Dual Progressive Transformations for Weakly Supervised Semantic SegmentationCode1
Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic SegmentationCode1
Background Activation Suppression for Weakly Supervised Object Localization and Semantic SegmentationCode1
Complementary Patch for Weakly Supervised Semantic SegmentationCode1
Conditional Diffusion Models for Weakly Supervised Medical Image SegmentationCode1
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic SegmentationCode1
Context Decoupling Augmentation for Weakly Supervised Semantic SegmentationCode1
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
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