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Found 3 papers, 1 papers with code
A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond
Masked autoencoders are scalable vision learners, as the title of MAE \cite{he2022masked}, which suggests that self-supervised learning (SSL) in vision might undertake a similar trajectory as in NLP.
PT4AL: Using Self-Supervised Pretext Tasks for Active Learning
Before the active learning iterations, the pretext task learner is trained on the unlabeled set, and the unlabeled data are sorted and split into batches by their pretext task losses.
Ranked #2 on
Active Learning
on CIFAR10 (10,000)
Incremental Object Grounding Using Scene Graphs
This paper aims to disambiguate the human's referring expressions by allowing the agent to ask relevant questions based on semantic data obtained from scene graphs.
