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Image Style Transfer Using Convolutional Neural Networks
Rendering the semantic content of an image in different styles is a difficult image processing task. Arguably, a major limiting factor for previous approaches has been the lack of imageExpand
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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. Thus far theExpand
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Texture Synthesis Using Convolutional Neural Networks
Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition. Samples from the model are of high perceptual qualityExpand
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Controlling Perceptual Factors in Neural Style Transfer
Neural Style Transfer has shown very exciting results enabling new forms of image manipulation. Here we extend the existing method to introduce control over spatial location, colour information andExpand
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Understanding Low- and High-Level Contributions to Fixation Prediction
Understanding where people look in images is an important problem in computer vision. Despite significant research, it remains unclear to what extent human fixations can be predicted by low-levelExpand
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Preserving Color in Neural Artistic Style Transfer
This note presents an extension to the neural artistic style transfer algorithm (Gatys et al.). The original algorithm transforms an image to have the style of another given image. For example, aExpand
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Deep convolutional models improve predictions of macaque V1 responses to natural images
Despite great efforts over several decades, our best models of primary visual cortex (V1) still predict spiking activity quite poorly when probed with natural stimuli, highlighting our limitedExpand
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Texture synthesis and the controlled generation of natural stimuli using convolutional neural networks
It is a long standing question how biological systems transform visual inputs to robustly infer high-level visual information. Research in the last decades has established that much of the underlyingExpand
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What does it take to generate natural textures?
Natural image generation is currently one of the most actively explored fields in Deep Learning. Many approaches, e.g. for state-of-the-art artistic style transfer or natural texture synthesis, relyExpand
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Deep convolutional models improve predictions of macaque V1 responses to natural images
Despite great efforts over several decades, our best models of primary visual cortex (V1) still predict spiking activity quite poorly when probed with natural stimuli, highlighting our limitedExpand
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