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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 171180 of 296 papers

TitleStatusHype
Weakly-Supervised Semantic Segmentation with Visual Words Learning and Hybrid PoolingCode0
Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation ModelsCode0
WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain LabelsCode0
MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation0
Neural Diffusion Distance for Image Segmentation0
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation0
NoPeopleAllowed: The Three-Step Approach to Weakly Supervised Semantic Segmentation0
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach0
One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model0
Generating Self-Guided Dense Annotations for Weakly Supervised Semantic Segmentation0
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