FaceResNet arch is different from the referenced paper?
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f-izzat commented
Looking at the code, why is there an SE module and why was it not referenced in the DocFace paper?, From my limited understanding of tf-slim, does the following
with slim.arg_scope([slim.batch_norm, slim.dropout], is_training=phase_train):
print('input shape:', [dim.value for dim in images.shape])
net = conv_module(images, 0, [32, 64], scope='conv1')
print('module_1 shape:', [dim.value for dim in net.shape])
net = conv_module(net, 2, [64, 128], scope='conv2')
print('module_2 shape:', [dim.value for dim in net.shape])
net = conv_module(net, 4, [128, 256], scope='conv3')
print('module_3 shape:', [dim.value for dim in net.shape])
net = conv_module(net, 10, [256, 512], scope='conv4')
print('module_4 shape:', [dim.value for dim in net.shape])
net = conv_module(net, 6, [512], scope='conv5')
print('module_5 shape:', [dim.value for dim in net.shape])
actually use batch_norm
and dropout
in the model at all? How does the model know when and where to create the mentioned layers?