“GAN-based AI Drawing Board for Image Generation and Colorization” by Li, Gou, Gong, Xiao and Han

  • ©Minghao Li, Yuchuan Gou, Bo Gong, Jing Xiao, and Mei Han

  • ©Minghao Li, Yuchuan Gou, Bo Gong, Jing Xiao, and Mei Han

  • ©Minghao Li, Yuchuan Gou, Bo Gong, Jing Xiao, and Mei Han

Conference:


Entry Number: 45

Title:

    GAN-based AI Drawing Board for Image Generation and Colorization

Presenter(s)/Author(s):



Abstract:


    We propose a GAN(Generative Adversarial Networks)-based drawing board which takes the semantic (by segmentation) and color tone (by strokes) inputs from users and automatically generates paintings. Our approach is built on a novel and lightweight feature embedding which incorporates the colorization effects into the painting generation process. Unlike the existing GAN-based image generation models which take semantics input, our drawing board has the ability to edit the local colors after generation. Our method samples the color information from users’ strokes as extra input, then feeds it into a GAN model for conditional generation. We enable the creation of pictures or paintings with semantics and color control in real-time.

Keyword(s):



Additional Images:

©Minghao Li, Yuchuan Gou, Bo Gong, Jing Xiao, and Mei Han ©Minghao Li, Yuchuan Gou, Bo Gong, Jing Xiao, and Mei Han

PDF:



ACM Digital Library Publication:



Overview Page:


Type: