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Relational Embedding for Few-Shot Classification

Introduction

Name: RENet
Embed.: ResNet12
Type: Fine-tuning
Venue: ICCV'21
Codes: renet

Cite this work with:

@article{DBLP:journals/corr/abs-2108-09666,
  author    = {Dahyun Kang and
               Heeseung Kwon and
               Juhong Min and
               Minsu Cho},
  title     = {Relational Embedding for Few-Shot Classification},
  journal   = {CoRR},
  volume    = {abs/2108.09666},
  year      = {2021},
}

Results and Models

Classification

Embedding 📖 miniImageNet (5,1) 💻 miniImageNet (5,1) 📖miniImageNet (5,5) 💻 miniImageNet (5,5) 📝 Comments
1 ResNet12 67.60 ± 0.44 66.83 ± 0.36 ⬇️ 📋 82.58 ± 0.30 82.13 ± 0.26 ⬇️ 📋 Reproduce
2 Conv64F - 57.62 ± 0.36 ⬇️ 📋 - 74.14 ± 0.27 ⬇️ 📋 Table.2
3 ResNet12 - 64.81 ± 0.37 ⬇️ 📋 - 79.90 ± 0.27 ⬇️ 📋 Table.2
3 ResNet18 - 62.86 ± 0.37 ⬇️ 📋 - - Table.2
Embedding 📖 tieredImageNet (5,1) 💻 tieredImageNet (5,1) 📖tieredImageNet (5,5) 💻 tieredImageNet (5,5) 📝 Comments
1 ResNet12 71.61 ± 0.5 71.23 ± 0.42 ⬇️ 📋 85.28 ± 0.35 84.78 ± 0.29 ⬇️ 📋 Reproduce
2 Conv64F - 61.62 ± 0.40 ⬇️ 📋 - 76.74 ± 0.33⬇️ 📋 Table.2
3 ResNet12 - 70.14 ± 0.43 ⬇️ 📋 - 82.70 ± 0.31 ⬇️ 📋 Table.2
4 ResNet18 - 71.53 ± 0.43 ⬇️ 📋 - - ⬇️ 📋 Table.2