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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 141150 of 296 papers

TitleStatusHype
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma0
Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization0
L2G: A Simple Local-to-Global Knowledge Transfer Framework for Weakly Supervised Semantic SegmentationCode1
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against ThresholdsCode1
Importance Sampling CAMs for Weakly-Supervised SegmentationCode0
Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic SegmentationCode1
Regional Semantic Contrast and Aggregation for Weakly Supervised Semantic SegmentationCode1
WegFormer: Transformers for Weakly Supervised Semantic Segmentation0
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic SegmentationCode1
Weakly Supervised Semantic Segmentation using Out-of-Distribution DataCode0
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