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Greatest papers with code

Self-Supervised Learning For Few-Shot Image Classification

14 Nov 2019phecy/SSL-FEW-SHOT

In this paper, we proposed to train a more generalized embedding network with self-supervised learning (SSL) which can provide robust representation for downstream tasks by learning from the data itself.

CROSS-DOMAIN FEW-SHOT LEARNING FEW-SHOT IMAGE CLASSIFICATION SELF-SUPERVISED LEARNING

A Broader Study of Cross-Domain Few-Shot Learning

ECCV 2020 IBM/cdfsl-benchmark

Extensive experiments on the proposed benchmark are performed to evaluate state-of-art meta-learning approaches, transfer learning approaches, and newer methods for cross-domain few-shot learning.

CROSS-DOMAIN FEW-SHOT LEARNING FEW-SHOT IMAGE CLASSIFICATION TRANSFER LEARNING

Cross-Domain Few-Shot Learning with Meta Fine-Tuning

21 May 2020johncai117/Meta-Fine-Tuning

In our final results, we combine the novel method with the baseline method in a simple ensemble, and achieve an average accuracy of 73. 78% on the benchmark.

CROSS-DOMAIN FEW-SHOT LEARNING DATA AUGMENTATION DOMAIN ADAPTATION TRANSFER LEARNING

Cross-Domain Few-Shot Learning by Representation Fusion

13 Oct 2020ml-jku/chef

On the few-shot datasets miniImagenet and tieredImagenet with small domain shifts, CHEF is competitive with state-of-the-art methods.

CROSS-DOMAIN FEW-SHOT LEARNING DRUG DISCOVERY