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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 241250 of 296 papers

TitleStatusHype
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor SegmentationCode0
Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation ModelsCode0
WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain LabelsCode0
A Multimodal Approach Combining Structural and Cross-domain Textual Guidance for Weakly Supervised OCT SegmentationCode0
Towards Single Stage Weakly Supervised Semantic SegmentationCode0
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic SegmentationCode0
All-pairs Consistency Learning for Weakly Supervised Semantic SegmentationCode0
Weakly Supervised Semantic Segmentation via Progressive Patch LearningCode0
Constrained-CNN losses for weakly supervised segmentationCode0
COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical imagesCode0
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