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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 101110 of 296 papers

TitleStatusHype
Non-Salient Region Object Mining for Weakly Supervised Semantic SegmentationCode1
SFC: Shared Feature Calibration in Weakly Supervised Semantic SegmentationCode1
Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic SegmentationCode1
Learning Integral Objects With Intra-Class Discriminator for Weakly-Supervised Semantic SegmentationCode1
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic SegmentationCode1
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic SegmentationCode1
GETAM: Gradient-weighted Element-wise Transformer Attention Map for Weakly-supervised Semantic segmentationCode1
Group-Wise Learning for Weakly Supervised Semantic SegmentationCode1
Group-Wise Semantic Mining for Weakly Supervised Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation with Boundary ExplorationCode1
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