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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 191–200 of 296 papers

TitleStatusHype
LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes—0
eX-ViT: A Novel eXplainable Vision Transformer for Weakly Supervised Semantic Segmentation—0
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference—0
One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model—0
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma—0
Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization—0
Importance Sampling CAMs for Weakly-Supervised SegmentationCode0
WegFormer: Transformers for Weakly Supervised Semantic Segmentation—0
Weakly Supervised Semantic Segmentation using Out-of-Distribution DataCode0
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