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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

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Showing 276–296 of 296 papers

TitleStatusHype
Two-Phase Learning for Weakly Supervised Object Localization—0
Discovering Class-Specific Pixels for Weakly-Supervised Semantic SegmentationCode0
Webly Supervised Semantic Segmentation—0
A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation—0
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation—0
Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network—0
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach—0
Weakly Supervised Semantic Segmentation using Web-Crawled Videos—0
Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation—0
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation—0
Weakly-Supervised Semantic Segmentation using Motion Cues—0
Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation—0
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network—0
Semantic Component Analysis—0
Spatio-temporal video autoencoder with differentiable memoryCode0
STC: A Simple to Complex Framework for Weakly-supervised Semantic SegmentationCode0
Weakly Supervised Semantic Segmentation for Social Images—0
Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image SegmentationCode0
Fully Convolutional Multi-Class Multiple Instance LearningCode0
From Image-level to Pixel-level Labeling with Convolutional Networks—0
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