Comments (2)
Hi,
thanks for your interest in our work.
The correct implementation of our loss function is that reported in our source code. We made a little mistake by squaring the whole fraction in our paper. The L2 regularization term, instead, is added as weight regularizer in the EltWise Product Layer, as you can see in the model.py
file.
from mlnet.
Thanks, it makes sense to me now.
from mlnet.
Related Issues (20)
- Loading model error HOT 1
- can't use ratio and frac_ratio together Error HOT 2
- about your provided weights of ML-Net HOT 2
- about fine-tune on MIT1003 HOT 2
- About the multi layer HOT 4
- Reproducing results when training using only SALICON dataset HOT 6
- can you provide loss value curve ?
- pytorch HOT 3
- are vgg weights only being used for feature extraction? HOT 2
- ERROR HOT 5
- some question about training process。
- Exception: Layer weight shape (3, 3, 640, 64) not compatible with provided weight shape (64, 3, 3, 3) HOT 3
- Broken vgg16_weights.h5 link in README HOT 2
- ImportError: cannot import name 'Layer' from 'keras.layers.core' HOT 1
- How to learn the prior maps in your method?
- Incompatibility between weights of the model layers and vgg16_weights.h5 file!! HOT 1
- Layer weight shape (3, 3, 640, 64) not compatible with provided weight shape (64, 3, 3, 3) HOT 3
- Outputs must be theano variables or Out instances
- input
- Broken mlnet_salicon_weights.pkl link in README HOT 1
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