Unicolor: A unified framework for multi-modal colorization with transformer

Zhitong Huang, Nanxuan Zhao, Jing Liao

Research output: Contribution to journalArticlepeer-review

35 Citations (SciVal)

Abstract

We propose the first unified framework UniColor to support colorization in multiple modalities, including both unconditional and conditional ones, such as stroke, exemplar, text, and even a mix of them. Rather than learning a separate model for each type of condition, we introduce a two-stage colorization framework for incorporating various conditions into a single model. In the first stage, multi-modal conditions are converted into a common representation of hint points. Particularly, we propose a novel CLIP-based method to convert the text to hint points. In the second stage, we propose a Transformer-based network composed of Chroma-VQGAN and Hybrid-Transformer to generate diverse and high-quality colorization results conditioned on hint points. Both qualitative and quantitative comparisons demonstrate that our method outperforms state-of-the-art methods in every control modality and further enables multi-modal colorization that was not feasible before. Moreover, we design an interactive interface showing the effectiveness of our unified framework in practical usage, including automatic colorization, hybrid-control colorization, local recolorization, and iterative color editing. Our code and models are available at https://luckyhzt.github.io/unicolor.

Original languageEnglish
Article number205
JournalACM Transactions on Graphics
Volume41
Issue number6
Early online date30 Nov 2022
DOIs
Publication statusPublished - 31 Dec 2022

Keywords

  • color editing
  • colorization
  • multi-modal controls
  • transformer

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

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