Style Transfer
446 papers with code • 2 benchmarks • 16 datasets
Style transfer is the task of changing the style of an image in one domain to the style of an image in another domain.
( Image credit: A Neural Algorithm of Artistic Style )
Benchmarks
These leaderboards are used to track progress in Style Transfer
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Libraries
Use these libraries to find Style Transfer models and implementationsDatasets
DukeMTMC-reID
MPI Sintel
MPIIGaze
WikiArt
iKala
Touchdown Dataset
POP909
PASTEL
Subtasks
Most implemented papers
A Neural Algorithm of Artistic Style
In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image.
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
junyanz/pytorch-CycleGAN-and-pix2pix
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ICCV 2017
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs.
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
We consider image transformation problems, where an input image is transformed into an output image.
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
xunhuang1995/AdaIN-style
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ICCV 2017
Gatys et al. recently introduced a neural algorithm that renders a content image in the style of another image, achieving so-called style transfer.
Deep Photo Style Transfer
luanfujun/deep-photo-styletransfer
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CVPR 2017
This paper introduces a deep-learning approach to photographic style transfer that handles a large variety of image content while faithfully transferring the reference style.
Instance Normalization: The Missing Ingredient for Fast Stylization
DmitryUlyanov/texture_nets
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It this paper we revisit the fast stylization method introduced in Ulyanov et.
Universal Style Transfer via Feature Transforms
Yijunmaverick/UniversalStyleTransfer
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NeurIPS 2017
The whitening and coloring transforms reflect a direct matching of feature covariance of the content image to a given style image, which shares similar spirits with the optimization of Gram matrix based cost in neural style transfer.
Exploring the structure of a real-time, arbitrary neural artistic stylization network
magenta/magenta
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In this paper, we present a method which combines the flexibility of the neural algorithm of artistic style with the speed of fast style transfer networks to allow real-time stylization using any content/style image pair.
Deep Feature Consistent Variational Autoencoder
We present a novel method for constructing Variational Autoencoder (VAE).
Style Transfer from Non-Parallel Text by Cross-Alignment
shentianxiao/language-style-transfer
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NeurIPS 2017
We demonstrate the effectiveness of this cross-alignment method on three tasks: sentiment modification, decipherment of word substitution ciphers, and recovery of word order.
