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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 91100 of 296 papers

TitleStatusHype
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue GraphsCode1
Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology ImagesCode1
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event CamerasCode1
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic SegmentationCode1
Class Re-Activation Maps for Weakly-Supervised Semantic SegmentationCode1
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
FPR: False Positive Rectification for Weakly Supervised Semantic SegmentationCode1
Class Tokens Infusion for Weakly Supervised Semantic SegmentationCode1
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic SegmentationCode1
Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional NetworksCode1
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