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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 1120 of 296 papers

TitleStatusHype
Conditional Diffusion Models for Weakly Supervised Medical Image SegmentationCode1
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance SegmentationCode1
Affinity Attention Graph Neural Network for Weakly Supervised Semantic SegmentationCode1
Complementary Patch for Weakly Supervised Semantic SegmentationCode1
Context Decoupling Augmentation for Weakly Supervised Semantic SegmentationCode1
Adaptive Early-Learning Correction for Segmentation from Noisy AnnotationsCode1
Background Activation Suppression for Weakly Supervised Object Localization and Semantic SegmentationCode1
Class Re-Activation Maps for Weakly-Supervised Semantic SegmentationCode1
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