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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 211220 of 296 papers

TitleStatusHype
Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic SegmentationCode1
A Weakly-Supervised Semantic Segmentation Approach based on the Centroid Loss: Application to Quality Control and Inspection0
LID 2020: The Learning from Imperfect Data Challenge Results0
Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels0
Causal Intervention for Weakly-Supervised Semantic Segmentation0
Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance SegmentationCode1
Weakly-Supervised Semantic Segmentation via Sub-category ExplorationCode1
Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization0
Weakly Supervised Semantic Segmentation with Boundary ExplorationCode1
Splitting vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation0
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