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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 8190 of 296 papers

TitleStatusHype
MCTformer+: Multi-Class Token Transformer for Weakly Supervised Semantic SegmentationCode1
Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise0
Hierarchical Semantic Contrast for Weakly Supervised Semantic SegmentationCode1
CG-fusion CAM: Online segmentation of laser-induced damage on large-aperture optics0
Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic SegmentationCode1
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor SegmentationCode0
Conditional Diffusion Models for Weakly Supervised Medical Image SegmentationCode1
P-NOC: adversarial training of CAM generating networks for robust weakly supervised semantic segmentation priors0
Masked Collaborative Contrast for Weakly Supervised Semantic SegmentationCode0
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