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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 110 of 296 papers

TitleStatusHype
SPARS: Self-Play Adversarial Reinforcement Learning for Segmentation of Liver TumoursCode0
Exploring CLIP's Dense Knowledge for Weakly Supervised Semantic SegmentationCode2
Exploiting Inherent Class Label: Towards Robust Scribble Supervised Semantic SegmentationCode0
DOEI: Dual Optimization of Embedding Information for Attention-Enhanced Class Activation MapsCode0
Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images0
Multi-Label Prototype Visual Spatial Search for Weakly Supervised Semantic Segmentation0
FFR: Frequency Feature Rectification for Weakly Supervised Semantic SegmentationCode0
POT: Prototypical Optimal Transport for Weakly Supervised Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation via Progressive Confidence Region ExpansionCode0
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency RegularizationCode0
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