LocalAggregation
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Do you load the entire training dataset in the memory bank?
Thanks for this work.
There is one thing that is a bit unclear. Exactly what is stored in the memory bank? Do you store all the training images in there, or only a subset of images? It seems that you are loading the whole imagenet into the bank, which takes a lot of memory space. Since I am trying to reproduce on my PC, this is impossible. Is there a commendation on the lower bound of the dataset size that does not severely affect the result?
The memory bank stores the embeddings of all the training images.
To be clear, the memory bank is in the shape of 1.2M * 128, where 128 is the dimension of the embedding, and the 1.2M is the size of ImageNet.