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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 211–220 of 296 papers

TitleStatusHype
Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation—0
Dual-Augmented Transformer Network for Weakly Supervised Semantic Segmentation—0
Webly Supervised Semantic Segmentation—0
DIAL: Dense Image-text ALignment for Weakly Supervised Semantic Segmentation—0
Densify Your Labels: Unsupervised Clustering with Bipartite Matching for Weakly Supervised Point Cloud Segmentation—0
A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation—0
Semantic Component Analysis—0
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds—0
Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network—0
Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation—0
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