Comments (4)
@JoyLuo
Hi Joy,
Sorry for the late response.
-
The 'shake' of the verification loss may be due to the (x-y)^2 in the Square layer.
I have tried to add L2-norm Layer but it seems to harm the training process and loss some information. I did not try adding the BatchNorm, and I think it may work. -
Actually I have tried classification:verification = 1:0.1,1:0.01 and the result is similar or no better than 1:1. So I do not try more variants.
Thank you!
Zhedong
from 2016_person_re-id.
@layumi thanks for you kindly answer.
could you show me the figure of loss_dif your trained? it will tell me the right way about how to down the loss_dif.
thank you!
luoze
from 2016_person_re-id.
I just uploaded the training curve of the Market-1501. You may refer to it.
https://github.com/layumi/2016_person_re-ID/blob/master/market1501-train-curve.pdf
The top1_compare and objective_compare are for the verification loss.
from 2016_person_re-id.
dear @layumi
i see the curve from you link. thanks for you kindly help
from 2016_person_re-id.
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