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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 151–175 of 296 papers

TitleStatusHype
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic SegmentationCode0
Precision matters: Precision-aware ensemble for weakly supervised semantic segmentationCode0
PSDPM: Prototype-based Secondary Discriminative Pixels Mining for Weakly Supervised Semantic SegmentationCode0
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation ApproachCode0
Removing supervision in semantic segmentation with local-global matching and area balancingCode0
Rethinking Saliency-Guided Weakly-Supervised Semantic SegmentationCode0
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic SegmentationCode0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Self-Supervised Difference Detection for Weakly-Supervised Semantic SegmentationCode0
Self-supervised Scale Equivariant Network for Weakly Supervised Semantic SegmentationCode0
SPARS: Self-Play Adversarial Reinforcement Learning for Segmentation of Liver TumoursCode0
Spatio-temporal video autoencoder with differentiable memoryCode0
STC: A Simple to Complex Framework for Weakly-supervised Semantic SegmentationCode0
Tackling Ambiguity from Perspective of Uncertainty Inference and Affinity Diversification for Weakly Supervised Semantic SegmentationCode0
Towards Single Stage Weakly Supervised Semantic SegmentationCode0
Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image SegmentationCode0
Weakly Supervised Semantic Segmentation using Out-of-Distribution DataCode0
Weakly Supervised Semantic Segmentation via Progressive Patch LearningCode0
Weakly Supervised Semantic Segmentation via Progressive Confidence Region ExpansionCode0
Weakly-Supervised Semantic Segmentation with Visual Words Learning and Hybrid PoolingCode0
Weakly-Supervised Semantic Segmentation with Image-Level Labels: from Traditional Models to Foundation ModelsCode0
WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain LabelsCode0
MuSCLe: A Multi-Strategy Contrastive Learning Framework for Weakly Supervised Semantic Segmentation—0
Neural Diffusion Distance for Image Segmentation—0
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