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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

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Showing 211–220 of 296 papers

TitleStatusHype
SSA: Semantic Structure Aware Inference for Weakly Pixel-Wise Dense Predictions without Cost—0
Inferring the Class Conditional Response Map for Weakly Supervised Semantic SegmentationCode0
Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty—0
Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation—0
Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary—0
Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke—0
Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation—0
Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation—0
Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation—0
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds—0
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