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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 251–260 of 296 papers

TitleStatusHype
Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation—0
USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation—0
Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary—0
Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation—0
Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation—0
Background Noise Reduction of Attention Map for Weakly Supervised Semantic Segmentation—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
Attention Bridging Network for Knowledge Transfer—0
0-1 laws for pattern occurrences in phylogenetic trees and networks—0
Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation—0
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