G-U-N / ECCV22-FOSTER

The official implementation for ECCV22 paper: "FOSTER: Feature Boosting and Compression for Class-Incremental Learning" in PyTorch.
MIT License
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Why Bound has different results ? #13

Open ChenJunzhi-buaa opened 1 year ago

ChenJunzhi-buaa commented 1 year ago

Is "Bound" joint-training 100 classes?Why Bound has different results ? image

thank you!

ChenJunzhi-buaa commented 1 year ago

I use the same setting as below,but the joint training result is only 0.71 ? image

image

G-U-N commented 1 year ago

Bound means: incremental learning with all the old samples reserved. Different protocols with different incremental sessions, therefore, have different average accuracies.

ChenJunzhi-buaa commented 1 year ago

Thank you ! So,What is your exemplars manage policy?Herding or Reservoir sampling? What‘s more,in a batch of 128,what is the propotion of new data and old data? Or, is the batch_size only the number of new data?

ChenJunzhi-buaa commented 1 year ago

Bound means: incremental learning with all the old samples reserved. Different protocols with different incremental sessions, therefore, have different average accuracies.

Bound is the average acc of "incremental learning with all the old samples reserved? And the last acc of "incremental learning with all the old samples reserved", is about 70 ?