Linghan Cheung
Thanks to @laetitiaoist , I added a parameter pad=1 to brew.conv(), it did achieve the padding goal.
@peterneher I used brew.group_conv() to implement mobilenet and encountered same problem. When I tried to load the model exported to Android, the predictor didn't work. `RuntimeError: [enforce fail at operator.cc:30]...
@steven5401 I have tried it, it works! Thanks a lot! It seems that Caffe2 don't treat the input blobs, which are *_riv and *_rm, of SpatialBN as part of parameters...
I got the same problem @northeastsquare
Get the same question here.
@QQQYang Thanks for your contribution to implementing the Rank Loss. Have your re-implement the result on the paper? Or you just trained on your own dataset?
@QQQYang OK. Could you share the alternating-training script for RA-CNN. I will very appreciate.
@jzhaosc Thx, it helps a lot. Be careful of the epsilon guys.
@jens25 Hi, jens25. I have followed your steps, but it didn't work. The model just never converge. I skipped the initialization with the VGG weights and used Adam with lr=1e-4....
@ouceduxzk I am very appreciated for your message. I noticed that you have made some effort on re-implementing this paper. I am looking forward to communicating with you for some...