The artistic style of a painting is a subtle aesthetic judgment used by art historians for grouping and classifying artwork. The recently introduced ‘neural-style’ algorithm substantially succeeds in merging the perceived artistic style of one image or set of images with the perceived content of another. In light of this and other recent developments in image analysis via convolutional neural n...

We have shown that it is possible to achieve artistic style transfer within a purely image processing paradigm. This is in contrast to previous work that utilized deep neural networks to learn the difference between “style” and “content” in a painting. We leverage the work by Kwatra et. al. on texture synthesis to accomplish “style synthesis” from our given style images, building off the work o...

The artistic style of a painting is a subtle aesthetic judgment used by art historians for grouping and classifying artwork. The neural style algorithm introduced by Gatys et al. (2016) substantially succeeds in image style transfer, the task of merging the style of one image with the content of another. This work investigates the effectiveness of a style representation derived from the neural ...

Artistic rendering is a subset of non-photorealistic rendering with the intention of using artistic effects in rendered images. This paper looks at texture transfer as a generalized method to render digital images in artistic styles. Texture transfer algorithms transfer the source texture to a target image. Since artistic style is subjective, this algorithm has four adjustable parameters that a...

Convolutional Neural Networks and Graphics Processing Units have been at the core of a paradigm shift in computer vision research that some researchers have called “the algorithmic perception revolution.” This thesis presents the implementation and analysis of several techniques for performing artistic style transfer using a Convolutional Neural Network architecture trained for large-scale imag...

The artistic style (or artistic movement) of a painting is a rich descriptor that captures both visual and historical information about the painting. Correctly identifying the artistic style of a paintings is crucial for indexing large artistic databases. In this paper, we investigate the use of deep residual neural to solve the problem of detecting the artistic style of a painting and outperfo...

There are three major advancements in the area of neural style transfer. In 2015, the paper, A neural algorithm of artistic style [2], proposes an iterative algorithm for neural style transfer. In 2016, the paper, Perceptual losses for real-time style transfer and super-resolution [3], proposes a real-time neural style transfer algorithm. However, for this algorithm, we have to train a seperate...

In the past, manually re-drawing an image in a certain artistic style required a professional artist and a long time. Doing this for a video sequence single-handed was beyond imagination. Nowadays computers provide new possibilities. We present an approach that transfers the style from one image (for example, a painting) to a whole video sequence. We make use of recent advances in style transfe...