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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
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency RegularizationCode0
Inferring the Class Conditional Response Map for Weakly Supervised Semantic SegmentationCode0
Integral Object Mining via Online Attention AccumulationCode0
Joint Learning of Saliency Detection and Weakly Supervised Semantic SegmentationCode0
Learning Pseudo Labels for Semi-and-Weakly Supervised Semantic SegmentationCode0
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic SegmentationCode0
Leveraging Swin Transformer for Local-to-Global Weakly Supervised Semantic SegmentationCode0
Masked Collaborative Contrast for Weakly Supervised Semantic SegmentationCode0
MECPformer: Multi-estimations Complementary Patch with CNN-Transformers for Weakly Supervised Semantic SegmentationCode0
MSG-SR-Net: A Weakly Supervised Network Integrating Multi-Scale Generation and Super-Pixel Refinement for Building Extraction from High-Resolution Remotely Sensed ImageriesCode0
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