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If we choose K among batch the average loss for this loss term will be higher than if we choose K for each image separately, so we will have stronger penalty on hard negatives. You can imagine that most of the images in batch have only 'easy negatives' which will not impact the loss significantly and therefore it might be better to pay more attention to other images in a batch. This was our motivation, so we haven't tried separate image negatives selection
Thanks for sharing the citation from the paper. Yes, we used batch-K selection, not a separate selection for each image, the description in the paper is incorrect here :(
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