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View Code? Open in Web Editor NEWCode for our NeurIPS'19 paper "Learning Deep Bilinear Transformation for Fine-grained Image Representation"
Code for our NeurIPS'19 paper "Learning Deep Bilinear Transformation for Fine-grained Image Representation"
I don't understand the code in 'dbt.py', line 216 to 221.
How to get the divisor of 128 and 512? plz
Link for downloading pre-trained model does not work
When is open source code ?
Thanks you for your work.
The structure in the source code:
Line 442 in 40877de
The souce code shows that when stage_index == 3
or stage_index == 4
, in other words, the Block3
or Block4
two blocks only have SG(Semantic Grouping Layer) and GB(Group Bilinear Layer) modules.
Will there be a pytorch version of this?
Thanks!
hi,Thanks for your share!
but, when I dubug the module GroupConv(nn.Conv2D) like this code, I get this error output: 'symbol' object has no attribute 'diag'. May u tell me, how I can use this module Independently?
`
temp_model = GroupConv(2048, kernel_size=1, use_bias=False, width=224)
temp_model.initialize(mx.init.MSRAPrelu())
temp_input = nd.random.normal(-1, 1, shape=(2,3, 224, 224))
temp_output = temp_model(temp_input)
`
I am an newer for MXNET
why set differentiable=False, will it block the gradient of weight and bias.
(-1, 128)
, why is it 128
?2048
.Thanks for your sharing.
I have a problem: why train_data processing is different from val_data processing when they are got through interface of ImageRecordIter.
Line 101 in 40877de
self.bias
and the self.weight
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