demonstration

AI Painting: An Aesthetic Painting Generation System

Authors:

Cunjun Zhang,

Kehua Lei,

Jia Jia,

Yihui Ma,

Zhiyuan HuAuthors Info & Claims

MM '18: Proceedings of the 26th ACM international conference on Multimedia

Pages 1231 - 1233

https://doi.org/10.1145/3240508.3241386

Published: 15 October 2018 Publication History

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Abstract

There are many great works done in image generation. However, it is still an open problem how to generate a painting, which is meeting the aesthetic rules in specific style. Therefore, in this paper, we propose a demonstration to generate a specific painting based on users' input. In the system called AI Painting, we generate an original image from content text, transfer the image into a specific aesthetic effect, simulate the image into specific artistic genre, and illustrate the painting process.

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Cited By

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Daryanavard Chounchenani MShahbahrami AHassanpour RGaydadjiev G(2025)Deep Learning Based Image Aesthetic Quality Assessment- A ReviewACM Computing Surveys10.1145/371682057:7(1-36)Online publication date: 21-Feb-2025
https://dl.acm.org/doi/10.1145/3716820
Carrasco MGonzález-Martín CNavajas-Torrente SDastres R(2024)Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological ProposalElectronics10.3390/electronics1320401413:20(4014)Online publication date: 12-Oct-2024
https://doi.org/10.3390/electronics13204014
Jiang YYu LMa JHu YFan GLi HHui P(2024)Digital Mustard Garden: Revitalizing Freehand-ink-painting Teaching through Artistic ParticipationProceedings of the 17th International Symposium on Visual Information Communication and Interaction10.1145/3678698.3687184(1-8)Online publication date: 11-Dec-2024
https://dl.acm.org/doi/10.1145/3678698.3687184
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Index Terms

AI Painting: An Aesthetic Painting Generation System
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Graphical user interfaces
  2. Interaction design
    1. Interaction design process and methods
      1. User interface design

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Information

Published In

MM '18: Proceedings of the 26th ACM international conference on Multimedia

October 2018

2167 pages

ISBN:9781450356657

DOI:10.1145/3240508

General Chairs:
Susanne Boll
University of Oldenburg, Germany
,
Kyoung Mu Lee
Seoul National University, Korea
,
Jiebo Luo
University of Rochester, USA
,
Wenwu Zhu
Tsinghua University, China
,
Program Chairs:
Hyeran Byun
Yonsei University, Korea
,
Chang Wen Chen
State Univ. Of New York at Buffalo, USA
,
Rainer Lienhart
University of Augsburg, Germany
,
Tao Mei
JD AI, China

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 October 2018

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Funding Sources

National Key Research and Develop- ment Plan
the Innovation Method Fund of China

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MM '18

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SIGMM

MM '18: ACM Multimedia Conference

October 22 - 26, 2018

Seoul, Republic of Korea

Acceptance Rates

MM '18 Paper Acceptance Rate 209 of 757 submissions, 28%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Daryanavard Chounchenani MShahbahrami AHassanpour RGaydadjiev G(2025)Deep Learning Based Image Aesthetic Quality Assessment- A ReviewACM Computing Surveys10.1145/371682057:7(1-36)Online publication date: 21-Feb-2025
https://dl.acm.org/doi/10.1145/3716820
Carrasco MGonzález-Martín CNavajas-Torrente SDastres R(2024)Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological ProposalElectronics10.3390/electronics1320401413:20(4014)Online publication date: 12-Oct-2024
https://doi.org/10.3390/electronics13204014
Jiang YYu LMa JHu YFan GLi HHui P(2024)Digital Mustard Garden: Revitalizing Freehand-ink-painting Teaching through Artistic ParticipationProceedings of the 17th International Symposium on Visual Information Communication and Interaction10.1145/3678698.3687184(1-8)Online publication date: 11-Dec-2024
https://dl.acm.org/doi/10.1145/3678698.3687184
Shi TChen CLi XHao A(2024)Semantic and style based multiple reference learning for artistic and general image aesthetic assessmentNeurocomputing10.1016/j.neucom.2024.127434582(127434)Online publication date: May-2024
https://doi.org/10.1016/j.neucom.2024.127434
San TKanematsu YMikami K(2023)Algorithmic Analysis of Color Combinations Principle in Game Concept ArtThe Journal of the Society for Art and Science10.3756/artsci.22.15_122:4(15_1-15_7)Online publication date: 2023
https://doi.org/10.3756/artsci.22.15_1
Xu JZhang XLi HYoo CPan Y(2023)Is Everyone an Artist? A Study on User Experience of AI-Based Painting SystemApplied Sciences10.3390/app1311649613:11(6496)Online publication date: 26-May-2023
https://doi.org/10.3390/app13116496
Yi RTian HGu ZLai YRosin P(2023)Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.02144(22388-22397)Online publication date: Jun-2023
https://doi.org/10.1109/CVPR52729.2023.02144
Bengamra SMzoughi OBigand AZagrouba E(2023)A comprehensive survey on object detection in Visual Art: taxonomy and challengeMultimedia Tools and Applications10.1007/s11042-023-15968-983:5(14637-14670)Online publication date: 3-Jul-2023
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Sun YLyu YLin PLin R(2022)Comparison of Cognitive Differences of Artworks between Artist and Artistic Style TransferApplied Sciences10.3390/app1211552512:11(5525)Online publication date: 29-May-2022
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Zhang JMiao YYu J(2021)A Comprehensive Survey on Computational Aesthetic Evaluation of Visual Art Images: Metrics and ChallengesIEEE Access10.1109/ACCESS.2021.30830759(77164-77187)Online publication date: 2021
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Digital Painting Techniques: Practical Techniques of Digital Art Masters

PAINTING FOR PHOTOGRAPHERS-Steps and Art Lessons for painting Photos in Corel Painter and Adobe Photoshop

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