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Dynamic closest color warping (DCCW) to measure the similarity between palettes by sorting palette colors and comparing the overall color flow.


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Dynamic Closest Color Warping to Sort and Compare Palettes

DCCW teaser

Dynamic Closest Color Warping to Sort and Compare Palettes
Suzi Kim and Sunghee Choi
Geometric Computing Lab., School of Computing, KAIST
Presented at ACM SIGGRAPH 2021

✨ This repo was given the replicability stamp by the Graphics Replicability Stamp Initiative (GRSI).


A color palette is one of the simplest and most intuitive descriptors that can be extracted from images or videos. This paper proposes a method to assess the similarity between color palettes by sorting colors. While previous palette similarity measures compare only colors without considering the overall palette combination, we sort palettes to minimize the geometric distance between colors and align them to share a common color tendency. We propose dynamic closest color warping (DCCW) to calculate the minimum distance sum between colors and the graph connecting the colors in the other palette. We evaluate the proposed palette sorting and DCCW with several datasets and demonstrate that DCCW outperforms previous methods in terms of accuracy and computing time. We validate the effectiveness of the proposed sorting technique by conducting a perceptual study, which indicates a clear preference for the results of our approach. We also demonstrate useful applications enabled by DCCW, including palette interpolation, palette navigation, and image recoloring.

How to Run


Our code is executed on top of the Docker container. Please go to the official docker installation guide if you don't already have Docker installed on your system.

Clone the Repository

git clone
cd DCCW 

Downloade the Dataset

git clone experiments/DCCW-dataset

Docker Setup

This repository provides a Dockerfile for setting up all dependencies. You can build and run a docker image by yourself.

mkdir user_data
docker-compose up --build

Now you can access localhost and see the DCCW website locally. Screenshot


Our paper is available at ACM Digital Library.
Paper thumbnails

Following supplemental materials are also available.

  • Supplemental material for acronym table, detailed related works, perceptual study analysis, and additional image recoloring results
  • Perceptual study questionnaire for SPS and PPS

Please cite with the following Bibtex code:

    title = {Dynamic Closest Color Warping to Sort and Compare Palettes},
    author = {Kim, Suzi and Choi, Sunghee},
    year = {2021},
    journal = {ACM Transactions on Graphics (Proceedings SIGGRAPH)},
    volume = {40},
    number = {4},
    articleno = {95},
    pages  = {1--15},
    address = {New York, NY, USA},
    doi = {10.1145/3450626.3459776},

You may also want to refer to our publication with the more MLA style:
Kim, Suzi, and Sunghee Choi. "Dynamic Closest Color Warping to Sort and Compare Palettes." ACM Transactions on Graphics (TOG) 40.4 (2021)


This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.2019-0-01158, Development of a Framework for 3D Geometric Model Processing)

Special Thanks

We've been inspired by many impressive color schemes uploaded on the Internet. We appreciate the designers who generate and share their incredible color schemes with us.


Contributions are always welcome! Don't heasitate to leave a question and issue on this github repo. Alternatively, drop us an e-mail at