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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 121130 of 296 papers

TitleStatusHype
Attention-based Class Activation Diffusion for Weakly-Supervised Semantic Segmentation0
Max Pooling with Vision Transformers reconciles class and shape in weakly supervised semantic segmentationCode1
Weakly Supervised Semantic Segmentation of Echocardiography Videos via Multi-level Features Selection0
SemFormer: Semantic Guided Activation Transformer for Weakly Supervised Semantic SegmentationCode1
SLAMs: Semantic Learning based Activation Map for Weakly Supervised Semantic Segmentation0
Hypergraph Convolutional Networks for Weakly-Supervised Semantic Segmentation0
WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain LabelsCode0
Dual Progressive Transformations for Weakly Supervised Semantic SegmentationCode1
Expansion and Shrinkage of Localization for Weakly-Supervised Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation via Progressive Patch LearningCode0
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