Download Few-Shot Datasets

All these datasets are only allowed to be downloaded by researchers for non-commercial research and educational purposes. As the miniImageNet and tieredImageNet are sampled from the ImageNet dataset, you need agree to the terms of ImageNet:

You (the "Researcher") have requested permission to use the ImageNet database (the "Database") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:

1. Researcher shall use the Database only for non-commercial research and educational purposes.
2. Princeton University and Stanford University make no representations or warranties regarding the Database, including but not limited to warranties of non-infringement or fitness for a particular purpose.
3. Researcher accepts full responsibility for his or her use of the Database and shall defend and indemnify the ImageNet team, Princeton University, and Stanford University, including their employees, Trustees, officers and agents, against any and all claims arising from Researcher's use of the Database, including but not limited to Researcher's use of any copies of copyrighted images that he or she may create from the Database.
4. Researcher may provide research associates and colleagues with access to the Database provided that they first agree to be bound by these terms and conditions.
5. Princeton University and Stanford University reserve the right to terminate Researcher's access to the Database at any time.
6. If Researcher is employed by a for-profit, commercial entity, Researcher's employer shall also be bound by these terms and conditions, and Researcher hereby represents that he or she is fully authorized to enter into this agreement on behalf of such employer.
7. The law of the State of New Jersey shall apply to all disputes under this agreement.

Please note that the splits for miniImageNet follow Ravi and Larochelle. Actually, there are two different kinds of splits for miniImageNet. See details here.

The download links are as follows:

miniImageNet: [Google Drive] [百度网盘] (提取码: xcu4) train.tar 125.9MB md5sum: 62af9b3c839974dad2d474e6325795af
val.tar 30.8MB md5sum: ab02f050b0bf66823e7acb0c1ac1bc6b
test.tar 39.2MB md5sum: 318185fc3e3bf8bc57de887d9682c666
tieredImageNet: [Google Drive] [百度网盘] (提取码: f269) tiered_imagenet.tar 19.4GB md5sum: 7828a6dc2889e226ba575d2ba9624753
Fewshot-CIFAR100: [Google Drive] [百度网盘] (提取码: 3mlb) train.tar 157.1MB md5sum: 80462b3ab41a97cd57f401bceb2a829d
val.tar 53.9MB md5sum: 2fe6624b1561e947e7fd55a49b4a342f
test.tar 53.6MB md5sum: 93b082e2bbb434299a1cff8f5fa6a331


[1] Russakovsky et al. “Imagenet large scale visual recognition challenge.” IJCV 2015;
[2] Krizhevsky et al. “Learning multiple layers of features from tiny images.” Technical report, University of Toronto, 2009.