Abstract
Recent advances in deep learning based algorithms have made it feasible to transfer image styles from an example image to other images. However, it is still hard to transfer the style of color sketches due to their unique texture statistics. In this paper, an automatic color sketch generation system is developed from existing real-time style transfer methods. We choose a suitable image from a set of carefully selected color sketch examples as the style target for every content image during training. We also propose a novel style transfer convolutional neural network with spatial refinement to realize high-resolution style transfer. Finally, gouache color is introduced to the generated images via a linear color transform followed by a guided filtering operation. Experimental results illustrate that our system can produce vivid color sketch images and greatly reduce artifacts compared to previous state-of-the-art methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
