Comments (1)
Thanks for your interests in my work!
Plan to update training code: Recently I'm quite busy with my classes (I'm a first-year PhD anyway :-)), but I will try to clean up the training code in half a month or so.
Details for training: With a single Pascal Titan X, it takes about one week for the network to fully converge and half a day to get reasonably good results. The memory usage depends on the batch size. I use batch size = 8 and it requires ~10G memory, but smaller batch size can give you similar results.
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Related Issues (20)
- What is the final training output HOT 1
- An error when running the test.lua without GPU HOT 5
- Style transfer between any two images - iOS App needs beta tester
- caffe model for vgg_normalised and decoder
- AdaIN-style iOS App HOT 5
- Prototxt file of vgg_normalised.caffemodel HOT 1
- backward on std_net HOT 1
- Congratulations to your ICCV paper
- Cuda is a dependency even when opt.GPU equals 0
- Trouble implementing AdaIn HOT 2
- reconStyle?
- Style_loss is normalized by batch_size twice HOT 1
- HI XunHuan I have issue run on my mac. HOT 1
- Testing performance
- TensorFlow implementation HOT 6
- Getting the weights of pretrained network HOT 1
- Implementation in C#
- Fix for Total Variational Loss
- Color saturation? HOT 1
- Why add the 3*3*1*1 conv0 layer in the encoder
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