Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer, Supplementary Material

نویسندگان

  • Xin Wang
  • Geoffrey Oxholm
  • Da Zhang
  • Yuan-Fang Wang
چکیده

Two additional figures are provided to demonstrate the superior performance of multimodal transfer and compare it to the state-of-the-art network by Johnson et al.(Johnson Net). In Fig. B, we show multimodal transfer results for many different styles on a large variety of contents. In Fig. C, we evaluate multimodal transfer on larger images (1800×1352) and compare the results with those of Johnson Net, illustrating the advantages of multimodal transfer in simulating both high-level texture and fine detailed brushwork of the original style guides.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Exploration of Style Transfer Using Deep Neural Networks

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...

متن کامل

Fast Patch-based Style Transfer of Arbitrary Style

Artistic style transfer is an image synthesis problem where the content of an image is reproduced with the style of another. Recent works show that a visually appealing style transfer can be achieved by using the hidden activations of a pretrained convolutional neural network. However, existing methods either apply (i) an optimization procedure that works for any style image but is very expensi...

متن کامل

Real-time Image Style Transfer

Artistic style transfer has long been an interesting topic in computer vision research. Recently several methods for style transfer based on convolutional neural networks have been proposed. This project aims at understanding and implementing some of the existing methods. More specifically we succeed in implementing the optimization based neural algorithm as well as the real-time style transfer...

متن کامل

Towards Deep Style Transfer: A Content-Aware Perspective

Recently, it has been shown that one can invert a deep convolutional neural network originally trained for classification tasks to transfer image style. There is, however, a dearth of research on content-aware style transfer. In this paper, we generalize the original neural algorithm [1] for style transfer from two perspectives: where to transfer and what to transfer. To specify where to transf...

متن کامل

Artistic Style Transfer

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...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017