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Semi-Supervised Semantic Segmentation

Models that are trained with a small number of labeled examples and a large number of unlabeled examples and whose aim is to learn to segment an image (i.e. assign a class to every pixel).

Papers

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Showing 111–120 of 190 papers

TitleStatusHype
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial LearningCode0
n-CPS: Generalising Cross Pseudo Supervision to n Networks for Semi-Supervised Semantic Segmentation—0
Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation—0
Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization—0
A Survey on Semi-Supervised Semantic Segmentation—0
BoundMatch: Boundary detection applied to semi-supervised segmentation for urban-driving scenes—0
C3-SemiSeg: Contrastive Semi-Supervised Segmentation via Cross-Set Learning and Dynamic Class-Balancing—0
CFCG: Semi-Supervised Semantic Segmentation via Cross-Fusion and Contour Guidance Supervision—0
Colour augmentation for improved semi-supervised semantic segmentation—0
Consistency Regularisation in Varying Contexts and Feature Perturbations for Semi-Supervised Semantic Segmentation of Histology Images—0
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