Meta-Album (Multi-domain Meta-Dataset for Few-Shot Image Classification)

Meta Album is a meta-dataset created for few-shot learning, meta-learning, continual learning and so on. Meta Album consists of 40 datasets from 10 unique domains. Datasets are arranged in sets (10 datasets, one dataset from each domain). It is a continuously growing meta-dataset.

We repurposed datasets that were generously made available by original creators. All datasets are free for use for academic purposes, provided that proper credits are given. For your convenience, you may cite our paper, which references all original creators.

Meta-Album is released under a CC BY-NC 4.0 license permitting non-commercial use for research purposes, provided that you cite us. Additionally, redistributed datasets have their own license.

The recommended use of Meta-Album is to conduct fundamental research on machine learning algorithms and conduct benchmarks, particularly in: few-shot learning, meta-learning, continual learning, transfer learning, and image classification.