@CVPR2018: Efficient unrolling iterative matrix square-root normalized ConvNets, implemented by PyTorch (and code of B-CNN,Compact bilinear pooling etc.) for training from scratch & finetuning.
I have notice a problem in finetune.sh
if i don't change setting the model used is this:
(features): WITH ALL LAYER
(classifier): Linear(in_features=32896, out_features=70, bias=True)
(representation): MPNCOV()
I don't understand why representation level is after classifier.
I have notice a problem in finetune.sh if i don't change setting the model used is this: (features): WITH ALL LAYER (classifier): Linear(in_features=32896, out_features=70, bias=True) (representation): MPNCOV()
I don't understand why representation level is after classifier.