SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 11–20 of 28 papers

TitleStatusHype
CMVAE: Causal Meta VAE for Unsupervised Meta-LearningCode0
Multi-level Second-order Few-shot LearningCode0
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-LearningCode0
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot TasksCode0
Self-Supervised Learning For Few-Shot Image ClassificationCode0
Unsupervised Meta-Learning via Latent Space Energy-based Model of Symbol Vector Coupling—0
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
Show:102550
← PrevPage 2 of 3Next →

No leaderboard results yet.