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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 271280 of 296 papers

TitleStatusHype
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
BroadCAM: Outcome-agnostic Class Activation Mapping for Small-scale Weakly Supervised ApplicationsCode0
Integral Object Mining via Online Attention AccumulationCode0
Inferring the Class Conditional Response Map for Weakly Supervised Semantic SegmentationCode0
Self-Supervised Difference Detection for Weakly-Supervised Semantic SegmentationCode0
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency RegularizationCode0
HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide ImagesCode0
Self-supervised Scale Equivariant Network for Weakly Supervised Semantic SegmentationCode0
Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic SegmentationCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
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