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Instance Normalization: The Missing Ingredient for Fast Stylization

2016-07-27 · Dmitry Ulyanov, Andrea Vedaldi, Victor Lempitsky

It this paper we revisit the fast stylization method introduced in Ulyanov et. al. (2016). We show how a small change in the stylization architecture results in a significant qualitative improvement in the generated images. The change is limited to swapping batch normalization with instance normalization, and to apply the latter both at training and testing times. The resulting method can be used to train high-performance architectures for real-time image generation. The code will is made available on github at https://github.com/DmitryUlyanov/texture_nets. Full paper can be found at arXiv:1701.02096.

📄 PDF Abstract BibTeX arXiv:1607.08022

Code (22)

DmitryUlyanov/texture_nets 공식 구현 torch
Chad4545/styletransfer pytorch
HarmanDotpy/Normalizations-in-Deep-Learning pytorch
MarvinLavechin/imagetranslation-tensorflow tf
Net-Mist/style-transfer-tf2 tf
aryan-mann/style-transfer
brightyoun/Video-Style-Transfer pytorch
buddly27/stylish
cryu854/FastStyle tf
cryu854/SinGAN tf
etttttte/mayfest2018 pytorch
hollygrimm/cyclegan-keras-art-attrs
jcjohnson/fast-neural-style torch
labmlai/annotated_deep_learning_paper_implementations pytorch
lengstrom/fast-style-transfer tf
milmor/perceptual-losses-neural-style tf
riven314/PerceptualLoss-FastAI pytorch
samwatts98/Fast-Neural-Style-Transfer-with-Laplacian-Loss-TensorFlow-1.13 tf
sundogai/style-transfer tf
tbullmann/imagetranslation-tensorflow tf
the-super-toys/glimpse-models pytorch
yakhyo/Fast-Neural-Style-Transfer pytorch

Tasks

Image GenerationImage StylizationStyle Transfer

Methods 이 논문이 사용한 방법론

Instance Normalization Instance Normalization (also known as contrast normalization) is a normalization layer where: $$ y_{tijk} = \frac{x_{tijk} - \mu_{ti}}{\sqrt{\sigma_{ti}^2 +…
Batch Normalization 설명 없음

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