Call for Papers

As an innovative engine for digital content generation, AI-Generated Content (AIGC) has drawn more and more attention from academic fields as well as industries. Specifically in the area of art creation, AI has demonstrated its great potential and gained increasing popularity. People are greatly impressed by AI painting, composing, writing, and design. The emerging technologies of the metaverse even provide more opportunities for AI art. AI has not only exhibited a certain degree of creativity, but also helped in uncovering the principles and mechanisms of creativity and imagination from the perspective of neuroscience, cognitive science, and psychology.

This is the 5^th AIART workshop to be held in conjunction with ICME 2023 in Brisbane, Australia, and it aims to bring forward cutting-edge technologies and most recent advances in the area of AI art in terms of enabling creation, analysis, understanding, and rendering technologies.

The theme topic of AIART 2023 will be AI for Creative Synergy. We plan to invite 5 keynote speakers to present their insightful perspectives on AI art.

We sincerely invite high-quality papers presenting or addressing issues related to AI art, including but not limited to the following topics:

• Affective computing for AI Art
• Theory and practice of AI creativity
• Neuroscience, cognitive science and psychology for AI Art
• AI Art for metaverse
• AI for painting generation
• AI for 3D content generation
• AI for cultural heritage
• AI for music/ sound synthesis, composition, performance, retrieval and instrument design
• AI for poem composing and synthesis
• AI for typography and graphic design
• AI for fashion, makeup, and digital humans
• AI for multimodal and cross-modal art generation
• AI for art style transfer
• AI for aesthetics understanding, analysis, assessment and prediction
• Authentication and copyright issues of AI artworks

The authors of selected high-quality papers will be invited to submit an extended version to the Machine Intelligence Research (MIR) journal published by Springer.

Additionally, one Best Paper Award will be given.

AIART 2023 is also launching a demo track for artists to showcase their creative artworks in the form of in-person or online gallery. The demo track will provide a great opportunity for people to experience interactive artworks and communicate creative ideas. The submission guideline for the demo track follows that of the main ICME conference: https://www.2023.ieeeicme.org/demonstrations.php.

Paper Submission

Authors should prepare their manuscript according to the Guide for Authors of ICME available at Author Information and Submission Instructions: https://www.2023.ieeeicme.org/author-info.php

Submission address: https://cmt3.research.microsoft.com/ICMEW2023

Keynotes (1/5)

Keynote 1

Speaker:

Brian C. Lovell

Title:

Synthesizing Faces for Ethical Face Recognition using Stable Diffusion

Time:

8:35 – 9:05, July 14, 2023

Abstract:

We propose a solution to address ethical concerns in face recognition databases by synthesizing faces to replace internet-scraped photographs without consent. Our approach utilizes generative techniques, including StyleGAN and Stable Diffusion. StyleGAN generates diverse and realistic synthetic faces by learning from extensive data, allowing control over facial attributes for demographic alignment. Stable Diffusion models image generation dynamics, producing high-quality, visually coherent synthetic faces. Our solution preserves database functionality while respecting privacy. Through evaluations, we assess visual quality, diversity, and demographic fairness of synthesized faces. Compatibility and effectiveness in face recognition tasks are also evaluated to maintain system accuracy and robustness. Our research highlights the potential of ethical face synthesis for creating privacy-preserving face recognition databases.

Biography:

Brian C. Lovell was born in Brisbane, Australia in 1960. He received the BE in electrical engineering in 1982, the BSc in computer science in 1983, and the PhD in signal processing in 1991: all from the University of Queensland (UQ). Professor Lovell is Director of the Advanced Surveillance Group in the School of ITEE, UQ. He was President of the International Association for Pattern Recognition (IAPR) [2008-2010], and is Fellow of the IAPR, Senior Member of the IEEE, and voting member for Australia on the Governing Board of the IAPR. He was General Co-Chair of the IEEE International Conference on Image Processing (ICIP) in Melbourne, 2013, Program Co-Chair of the International Conference of Pattern Recognition (ICPR) in Cancun, 2016, and Program Co-Chair of ICPR2020 in Milan. His interests include Artificial Intelligence, Computer Vision, non-cooperative Face Recognition, Biometrics, and Pattern Recognition.

Keynotes (3/5)

Keynote 3

Speaker:

Kang Zhang

Title:

Creating a Massive Open Metaverse Course (MOMC)

Time:

13:30 – 14:00, July 14, 2023

Abstract:

Much effort has been made in using virtual reality (VR) technology to support massive open online course (MOOC) environments. This talk briefly reviews the latest research in VR/AR/XR application in education, and argues how immersive virtual educational experiences could be gained. We then introduce the new concept of Massive Open Metaverse Course (MOMC), combining MOOC and Metaverse and utilizing the latest volumetric video technology. We offer our vision on dual campus online education for HKUST 2.0, with a real case study, i.e., the President’s First Lecture, under development at the Guangzhou campus. This is the world’s first true MOMC environment, providing immersive and realistic virtual and augmented reality experiences to both teachers and learners.

Biography:

Kang Zhang is Acting Head and Professor of Computational Media and Arts, Information Hub, Hong Kong University of Science and Technology (Guangzhou), Professor of Division of Emerging Interdisciplinary Areas, HKUST, and Professor Emeritus of Computer Science, The University of Texas at Dallas. He was a Fulbright Distinguished Chair and an ACM Distinguished Speaker, and held academic positions in China, the UK, Australia and USA. Zhang's current research interests include computational aesthetics, visual languages, and generative art and design; and has published 8 books, and over 120 journal papers in these areas. He has delivered keynotes at art and design, computer science, and management conferences, and is on the editorial boards of Journal of Big Data, The Visual Computer, Journal of Visual Language and Computing, International Journal of Software Engineering and Knowledge Engineering, International Journal of Advanced Intelligence, and Visual Computing for Industry, Biomedicine, and Art.

Keynotes (5/5)

Keynote 5

Speaker:

Dong Liu

Title:

Controllable Image Synthesis with Diffusion Models

Time:

16:45 – 17:15, July 14, 2023

Abstract:

Diffusion models have demonstrated impressive capability in synthesizing photorealistic images given a few or even no words. These models may not fully satisfy user need, as normal users or artists intend to control the synthesized images with specific guidance, like overall layout, color, structure, object shape, and so on. We propose a method to adapt diffusion models for controllable image synthesis. Our method outperforms the existing methods and demonstrates multiple applications with its plausible generalization ability and flexible controllability.

Biography:

Dong Liu received the B.S. and Ph.D. degrees in electrical engineering from the University of Science and Technology of China (USTC), Hefei, China, in 2004 and 2009, respectively. He was a Member of Research Staff with Nokia Research Center, Beijing, China, from 2009 to 2012. He joined USTC as a faculty member in 2012 and became a Professor in 2020. His research interests include image and video processing, coding, analysis, and data mining. He has authored or co-authored more than 200 papers in international journals and conferences, which were cited more than 12000 times according to Google Scholar (h-index is 42). He has more than 30 granted patents. He has several technique proposals adopted by standardization groups. He received 2009 IEEE TCSVT Best Paper Award, VCIP 2016 Best 10% Paper Award, and ISCAS 2022 Grand Challenge Top Creativity Paper Award. He is a Senior Member of IEEE, CCF, and CSIG, an elected member of MSA-TC of IEEE CAS Society, and an elected member of Multimedia TC of CSIG. He serves or had served as the Chair of IEEE 1857.11 Standard Working Subgroup (also known as Future Video Coding Study Group), a Guest Editor for IEEE TCSVT, an Organizing Committee Member for VCIP 2022, ChinaMM 2022, ICME 2021, etc.

Technical Program Committee (Tentative)

• Ajay Kapur, California Institute of the Arts, USA
• Alan Chamberlain, University of Nottingham, Nottingham
• Alexander Lerch, Georgia Institute of Technology, USA
• Alexander Pantelyat, Johns Hopkins University, USA
• Bahareh Nakisa, Deakin University, Australia
• Baoqiang Han, China Conservatory of Music, China
• Baoyang Chen, Central Academy of Fine Arts, China
• Beici Liang, Tencent Music Entertainment Group, China
• Bing Li, King Abdullah University of Science and Technology, Saudi Arabia
• Björn W. Schuller, Imperial College London, UK
• Bob Sturm, KTH Royal Institute of Technology, Sweden
• Carlos Castellanos, Rochester Institute of Technology, USA
• Changsheng Xu, Institute of Automation, Chinese Academy of Sciences, China
• Dongmei Jiang, Northwestern Polytechnical University, China
• Emma Young, BBC, UK
• Gus Xia, New York University Shanghai, China & Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates
• Haifeng Li, Harbin Institute of Technology, China
• Haipeng Mi, Tsinghua University, China
• Hongxun Yao, Harbin Institute of Technology, China
• Jesse Engel, Google, USA
• Jia Jia, Tsinghua University, China
• Jianyu Fan, Microsoft, Canada
• Jing Wang, Beijing Institute of Technology, China
• John See, Multimedia University, Malaysia
• Juan Huang, Johns Hopkins University, USA
• Junping Zhang, Fudan University, China
• Kejun Zhang, Zhejiang University, China
• Ke Lv, University of Chinese Academy of Sciences, China
• Kenneth Fields, Central Conservatory of Music, China
• Lai-Kuan Wong, Multimedia University, Malaysia
• Lamtharn Hanoi Hantrakul, ByteDance, USA
• Lei Xie, Northwestern Polytechnical University, China
• Lin Gan, Tianjin University, China
• Long Ye, China University of Communication, China
• Maosong Sun, Tsinghua University, China
• Mei Han, Ping An Technology Art institute, USA
• Mengjie Qi, China Conservatory of Music, China
• Ming Zhang, Nanjing Art College, China
• Mohammad Naim Rastgoo, Queensland University of Technology, Australia
• Na Qi, Beijing University of Technology, China
• Nick Bryan-Kinns, Queen Mary University of London, UK
• Nina Kraus, Northwestern University, USA
• Pengtao Xie, University of California, San Diego, USA
• Philippe Pasquier, Simon Fraser University, Canada
• Qin Jin, Renmin University, China
• Qiuqiang Kong, ByteDance, China
• Rebecca Fiebrink, University of London, UK
• Rick Taube, University of Illinois at Urbana-Champaign, USA
• Roger Dannenberg, Carnegie Mellon University, USA
• Rongfeng Li, Beijing University of Posts and Telecommunications, China
• Rui Wang, Institute of Information Engineering, Chinese Academy of Sciences, China
• Ruihua Song, Renmin University, China
• Shangfei Wang, University of Science and Technology of China, China
• Shasha Mao, Xidian University, China
• Shiguang Shan, Institute of Computing Technology, Chinese Academy of Sciences, China
• Shiqi Wang, City University of Hong Kong, China
• Shun Kuremoto，Uchida Yoko Co.,Ltd，Japan
• Si Liu, Beihang University, China
• Simon Lui, Huawei Technologies Co., Ltd, China
• Tiange Zhou, NetEase Cloud Music, China
• Weibei Dou, Tsinghua University, China
• Weiming Dong, Institute of Automation, Chinese Academy of Sciences, China
• Wei-Ta Chu, National Chung Cheng University, Taiwan, China
• Wei Li, Fudan University, China
• Weiwei Zhang, Dalian Maritime University, China
• Wei Zhong, China University of Communication, China
• Wen-Huang Cheng, National Chiao Tung University, Taiwan, China
• Wenli Zhang, Beijing University of Technology, China
• Xi Shao, Nanjing University of Posts and Telecommunications, China
• Xiaojing Liang, NetEase Cloud Music, China
• Xiaopeng Hong, Harbin Institute of Technology, China
• Xiaoyan Sun, University of Science and Technology of China, China
• Xiaoying Zhang, China Rehabilitation Research Center, China
• Xihong Wu, Peking University, China
• Xinfeng Zhang, University of Chinese Academy of Sciences, China
• Xu Tan, Microsoft Research Asia, China
• Yanchao Bi, Beijing Normal University, China
• Yi Qin, Shanghai Conservatory of Music, China
• Ying-Qing Xu, Tsinghua University, China
• Yirui Wu, Hohai University, China
• Yuanchun Xu, Xiaoice, China
• Zhiyao Duan, University of Rochester, USA

History

• AIART 2019: https://aiart2019.github.io/
• AIART 2020: https://aiart2020.github.io/
• AIART 2021: https://aiart2021.github.io/
• AIART 2022: https://aiart2022.github.io/

Tezign has the vision Technology Empowers Imagination. Founded in 2015, Tezign aims to build the digital infrastructure of content experience. Tezign provides a digital platform based on enterprise content workflow, connecting content production, management and application, to help brands drive growth with content.

Tezign has raised the D1 round of financing and become the only Contech unicorn enterprise with a valuation of more than US $1 billion. Tezign is backed by world recognized investors including Temasek, Sequoia Capital, Hearst Ventures, among others. Tezign has partnered with more than 200 medium to large enterprises such as Alibaba, Unilever, ByteDance, PepsiCo, Shiseido, P&G, Starbucks, McDonald's, Heinz, Mars, Budweiser, Adidas, Xtep, Ubras, Lenovo, Midea, Tencent, L'Oreal, Danone, Porsche, Audi, Volvo, Aptar, Bosch, Stanley Black & Decker etc to upgrade their content strategies. It has produced more than 150,000 creative content assets and formed a one hundred million level content asset management scale. Tezign's content ecosystem has gathered more than 50,000 content creators.

Tezign was a National Industrial Design Center issued by the Ministry of industry and information technology, awarded as TOP.1 in China in the list of The Information 50 startups, Fast Company top 50 of China's best innovative companies, Forbes High Growth Gazelle, Forbes China Top 10 intelligent design enterprises, Hurun Group List of Global Unicorn, and was named by Forrester, a leading independent global technology and market research company, in the Research Report "Now Tech: Marketing Resource Management, Q12022" (MRM) as the only MRM vendor in the contech segment Asia Pacific.

On 6th-7th May 2023, Tezign will launch the AIGC Builder and Creator Conference in Shanghai, to create maximum two-way interaction among AIGC creators and builders in various quality forms. Stay tuned by following the official Wechat account: Who is AIGC.