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YyzHarry / imbalanced-semi-self

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
https://arxiv.org/abs/2006.07529
MIT License
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Have you ever tried "Semi-Supervised Imbalanced Learning on ImageNet-LT"? #18

Closed e96031413 closed 3 years ago

e96031413 commented 3 years ago

Hi, have you ever tried "Semi-Supervised Imbalanced Learning" on ImageNet-LT?

According to the experiment result in the paper, the performance with Semi-Supervised Imbalanced Learning seems better than Self-Supervised Imbalanced Learning on CIFAR-10-LT.

If I want to try this experiment, how can I modify the dataset/imagenet.py to dataset/imblance_imagenet.py (similar to imblance_cifar.py)?

YyzHarry commented 3 years ago

Hi, we did not try semi-supervised imbalanced learning on ImageNet-LT. The main reason is that we do not have a larger extra unlabeled dataset for it. FYI, CIFAR-10 has the TinyImages as the extra unlabeled dataset, as we descirbed in the paper.

I guess one way to include more unlabeled data could be using the unused data in the original ImageNet (since ImageNet-LT uses only a subset of ImageNet).

e96031413 commented 3 years ago

OK, Thanks for your reply