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征稿启事 | AIART 2024 Call for Papers

已有 355 次阅读 2024-3-12 17:41 |个人分类:征稿启事|系统分类:博客资讯

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今年7月,由MIR参与合作举办的学术会议AIART2024将在加拿大召开 (与ICME2024同期),Workshop现公开征稿中,并诚邀赞助!

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AIART 2024 Call for Papers

The 6th IEEE Workshop on Artificial Intelligence for Art Creation

Overview

Recent advances of AI-Generated Content (AIGC) have been an innovative engine for digital content generation. As an ever increasingly powerful tool, AI has gained great popularity across the whole spectrum of art, such as AI painting, composing, writing, virtual hosting, fashion, design, etc. Tools like Sora even demonstrates the ability to model and simulate the physical world. An era of AI-generated videos or movies is coming. Moreover, AI is also capable of understanding art, and evaluating the aesthetic value of art as well. AI has not only exhibited creativity to some extent, but also served as an enabling tool to discover the principles underneath creativity and imagination, which are traditional challenges for neuroscience, cognitive science, and psychology. Despite all these promising features of AI for Art, we still have to face the many challenges such as the explainability of generative models and the copyright issues of AI art works.

This is the 6th AIART workshop to be held in conjunction with ICME 2024 in Niagara Falls, Canada, 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 2024 will be Big Models for Art Creation. We plan to invite 3 keynote speakers to present their insightful perspectives on AI art.

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 2024 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://2024.ieeeicme.org/author-information-and-submission-instructions/.

Topics

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

1) Affective computing for AI Art

2) Theory and practice of AI creativity

3) Neuroscience, cognitive science and psychology for AI Art

4) Explainable AI (XAI) for art

5) AI Art for metaverse

6) AI for painting generation

7) AI for 3D content generation

8) AI for video and movie

9) AI for cultural heritage

10) AI for sound synthesis, music composition, performance, and instrument design

11) AI for poem composing and synthesis

12) AI for typography and graphic design

13) AI for fashion, makeup, and virtual hosting

14) AI for multimodal and cross-modal art generation

15) AI for art style transfer

16) AI for aesthetics understanding, analysis, assessment and prediction

17) Authentication and copyright issues of AI artworks

Submission

Authors should prepare their manuscript according to the Guide for Authors of ICME available at Author Information and Submission Instructions

https://2024.ieeeicme.org/author-information-and-submission-instructions/ 

Submission address: 

https://cmt3.research.microsoft.com/ICMEW2024

Important Dates

Submissions due:April 6, 2024

Workshop date:TBD

Homepage

https://aiart2024.github.io/

Technical Program Committee

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

Organizing Team

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Luntian Mou

Beijing University of Technology

Beijing, China

ltmou@bjut.edu.cn

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Feng Gao

Peking University

Beijing, China

gaof@pku.edu.cn

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Kejun Zhang

Zhejiang University

Hangzhou, China

zhangkejun@zju.edu.cn

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Jiaying Liu

Peking University

Beijing, China

liujiaying@pku.edu.cn

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Ling Fan

Tezign.com

Tongji University Design Artificial Intelligence Lab

Shanghai, China

lfan@tongji.edu.cn

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Zeyu Wang

Hong Kong University of Science and

Technology (Guangzhou)

Guangzhou, China

zeyuwang@ust.hk

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Nick Bryan-Kinns

University of the Arts London

London, UK

n.bryankinns@arts.ac.uk

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Ambarish Natu

Australian Government

Australian Capital Territory, Australia

ambarish.natu@gmail.com

Partner: Machine Intelligence Research

Machine Intelligence Research, published by Springer, and sponsored by Institute of Automation, Chinese Academy of Sciences, is formally released in 2022. The journal publishes high-quality papers on original theoretical and experimental research, targets special issues on emerging topics and specific subjects, and strives to bridge the gap between theoretical research and practical applications. The journal has been indexed by ESCI, EI, Scopus, CSCD, etc.

MIR official websites:

https://www.springer.com/journal/11633

https://www.mi-research.net

MIR Editor-in-Chief :

Tan Tieniu, Institute of Automation, Chinese Academy of Sciences

MIR Associate Editors-in-Chief:

Liang Wang, Chinese Academy of Sciences, China

Yike Guo, Imperial College London, UK

Brian C. Lovell, The University of Queensland, Australia

Call For Sponsorship

Platinum Level

- 4 free registrations (or including up to 4 full registration)

- Invitation to give an industry keynote speech

- Logo on AIART 2024 official website with description and link to sponsor website

- Logo on workshop handbook and presentation material (under Platinum Level)

- One on one negotiation for special requirements.

Gold Level

- 2 free registrations (or including up to 2 full registration)

- Participation in related industry panel

- Logo on AIART 2024 official website with short description and link to sponsor website

- Logo on workshop handbook and presentation material (under Gold Level)

- One on one negotiation for special requirements.

Silver Level

- 1 free registration (or including up to 1 full registration)

- Logo on AIART 2024 official website with link to sponsor website

- Logo on workshop handbook and presentation material (under Silver Level)

关于Machine Intelligence Research

Machine Intelligence Research(简称MIR,原刊名International Journal of Automation and Computing)由中国科学院自动化研究所主办,于2022年正式出版。MIR立足国内、面向全球,着眼于服务国家战略需求,刊发机器智能领域最新原创研究性论文、综述、评论等,全面报道国际机器智能领域的基础理论和前沿创新研究成果,促进国际学术交流与学科发展,服务国家人工智能科技进步。期刊入选"中国科技期刊卓越行动计划",已被ESCI、EI、Scopus、中国科技核心期刊、CSCD等数据库收录。

往期目录

2024年第1期 | 特约专题: AI for Art

2023年第6期 | 影像组学、机器学习、图像盲去噪、深度估计...

2023年第5期 | 生成式人工智能系统、智能网联汽车、毫秒级人脸检测器、个性化联邦学习框架... (机器智能研究MIR)

2023年第4期 | 大规模多模态预训练模型、机器翻译、联邦学习......

2023年第3期 | 人机对抗智能、边缘智能、掩码图像重建、强化学习... 

2023年第2期 · 特约专题 | 大规模预训练: 数据、模型和微调

2023年第1期 | 类脑智能机器人、联邦学习、视觉-语言预训练、伪装目标检测... 

2022年第6期 | 因果推理、视觉表征学习、视频息肉分割...

2022年第5期 | 重磅专题:类脑机器学习

2022年第4期 | 来自苏黎世联邦理工学院Luc Van Gool教授团队、清华大学戴琼海院士团队等

2022年第3期 | 聚焦自然语言处理、机器学习等领域;来自复旦大学、中国科学院自动化所等团队

2022年第2期 | 聚焦知识挖掘、5G、强化学习等领域;来自联想研究院、中国科学院自动化所等团队

主编谭铁牛院士寄语, MIR第一期正式出版!

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