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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 281290 of 296 papers

TitleStatusHype
ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical ImagesCode0
Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region GrowingCode0
Pixel-Level Domain Adaptation: A New Perspective for Enhancing Weakly Supervised Semantic SegmentationCode0
Fully Convolutional Multi-Class Multiple Instance LearningCode0
From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion ModelsCode0
Fine-grained Background Representation for Weakly Supervised Semantic SegmentationCode0
Weakly Supervised Semantic Segmentation via Progressive Confidence Region ExpansionCode0
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image DomainsCode0
SPARS: Self-Play Adversarial Reinforcement Learning for Segmentation of Liver TumoursCode0
FFR: Frequency Feature Rectification for Weakly Supervised Semantic SegmentationCode0
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