Interactive Style Transfer: All is Your Palette

TL;DR

This paper introduces an interactive style transfer method that allows users to creatively and precisely apply styles to images using a brush-like interface, enhancing artistic control over neural style transfer.

Contribution

The proposed method enables fine-grained, interactive style transfer with a fluid simulation algorithm, expanding the creative possibilities of neural style transfer.

Findings

Allows users to dip and paint styles interactively

Produces thousands of unique artworks from a single style image

Enhances artistic control in neural style transfer applications

Abstract

Neural style transfer (NST) can create impressive artworks by transferring reference style to content image. Current image-to-image NST methods are short of fine-grained controls, which are often demanded by artistic editing. To mitigate this limitation, we propose a drawing-like interactive style transfer (IST) method, by which users can interactively create a harmonious-style image. Our IST method can serve as a brush, dip style from anywhere, and then paint to any region of the target content image. To determine the action scope, we formulate a fluid simulation algorithm, which takes styles as pigments around the position of brush interaction, and diffusion in style or content images according to the similarity maps. Our IST method expands the creative dimension of NST. By dipping and painting, even employing one style image can produce thousands of eye-catching works. The demo video is available in supplementary files or in http://mmcheng.net/ist.