LearningToCompare

Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning

Howto

download 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

NOTICE

current 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-Imagenet

| Model | 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% | | |