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thanks for the great work! I have a question about how to compute feature compactness as shown in Figure 6 in the original paper. What I did is to get resnet features (4096 dimensional tensor) before FC layer for each ground truth class, and compute the averaged distance with it's centroid. But the distances I got is generally greater than 50, even 100, as opposed to what's in the paper (<0.5).
Could you share how you computed the compactness for each class?
Thanks,
Issac
The text was updated successfully, but these errors were encountered:
Hi,
thanks for the great work! I have a question about how to compute feature compactness as shown in Figure 6 in the original paper. What I did is to get resnet features (4096 dimensional tensor) before FC layer for each ground truth class, and compute the averaged distance with it's centroid. But the distances I got is generally greater than 50, even 100, as opposed to what's in the paper (<0.5).
Could you share how you computed the compactness for each class?
Thanks,
Issac
The text was updated successfully, but these errors were encountered: