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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 4150 of 296 papers

TitleStatusHype
MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic SegmentationCode1
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic SegmentationCode1
Extracting Class Activation Maps from Non-Discriminative Features as wellCode1
Token Contrast for Weakly-Supervised Semantic SegmentationCode1
Self Correspondence Distillation for End-to-End Weakly-Supervised Semantic SegmentationCode1
Class-incremental Continual Learning for Instance Segmentation with Image-level Weak SupervisionCode1
FPR: False Positive Rectification for Weakly Supervised Semantic SegmentationCode1
Boundary-Enhanced Co-Training for Weakly Supervised Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation via Adversarial Learning of Classifier and ReconstructorCode1
Weakly Supervised Semantic Segmentation for Large-Scale Point CloudCode1
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