Constrained Neural Style Transfer for Decorated Logo Generation

2 Mar 2018  ·  Gantugs Atarsaikhan, Brian Kenji Iwana, Seiichi Uchida ·

Making decorated logos requires image editing skills, without sufficient skills, it could be a time-consuming task. While there are many on-line web services to make new logos, they have limited designs and duplicates can be made. We propose using neural style transfer with clip art and text for the creation of new and genuine logos. We introduce a new loss function based on distance transform of the input image, which allows the preservation of the silhouettes of text and objects. The proposed method constrains style transfer only around the designated area. We demonstrate the characteristics of proposed method. Finally, we show the results of logo generation with various input images.

PDF Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here