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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 221–230 of 296 papers

TitleStatusHype
Towards Single Stage Weakly Supervised Semantic SegmentationCode0
ECS-Net: Improving Weakly Supervised Semantic Segmentation by Using Connections Between Class Activation Maps—0
Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image—0
3D Guided Weakly Supervised Semantic Segmentation—0
A Weakly-Supervised Semantic Segmentation Approach based on the Centroid Loss: Application to Quality Control and Inspection—0
LID 2020: The Learning from Imperfect Data Challenge Results—0
Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels—0
Causal Intervention for Weakly-Supervised Semantic Segmentation—0
Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization—0
Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation—0
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