LearningToCompare Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning
Howtodownload mini-imagenet and make it looks like:
mini-imagenet/
├── images
├── n0210891500001298.jpg
├── n0287152500001298.jpg
...
├── test.csv
├── val.csv
└── train.csv
LearningToCompare-Pytorch/
├── compare.py
├── MiniImagenet.py
├── Readme.md
├── repnet.py
├── train.py
└── utils.py python train.py NOTICEcurrent code support multi-gpus on single machine training, to disable it and train on single machine, just set device_ids=[0] and downsize batch size according to your gpu memory capacity. make sure ckpt
directory exists, otherwise mkdir ckpt
.
mini-ImagenetModel Fine Tune 5-way Acc. 20-way Acc 1-shot 5-shot 1-shot 5-shot Matching Nets N 43.56% 55.31% 17.31% 22.69% Meta-LSTM 43.44% 60.60% 16.70% 26.06% MAML Y 48.7% 63.11% 16.49% 19.29% Meta-SGD 50.49% 64.03% 17.56% 28.92% TCML 55.71% 68.88% - - Learning to Compare N 57.02% 71.07% - - Ours, similarity ensemble N 55.2% 68.8% Ours, feature ensemble N 55.2% 70.1%