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Unsupervised Few-Shot Image Classification

In contrast to (supervised) few-shot image classification, only the unlabeled dataset is available in the pre-training or meta-training stage for unsupervised few-shot image classification.

Papers

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Showing 11–20 of 28 papers

TitleStatusHype
Few-Shot Image Classification via Contrastive Self-Supervised Learning—0
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images—0
Invariant and consistent: Unsupervised representation learning for few-shot visual recognition—0
Meta-DM: Applications of Diffusion Models on Few-Shot Learning—0
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps—0
Unsupervised Few-shot Learning via Self-supervised Training—0
Unsupervised Learning via Meta-Learning—0
Unsupervised Meta-Learning For Few-Shot Image Classification—0
Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models—0
Unsupervised Meta-Learning via Latent Space Energy-based Model of Symbol Vector Coupling—0
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