ArtVerse: A Paradigm for Parallel Human–Machine Collaborative Painting Creation in Metaverses
Abstract
Currently, the development of the foundation model, metaverse, nonfungible token (NFT), and other emerging technologies has brought profound effects on the whole art field, including art creation, dissemination, transaction, etc. However, there is no research focusing on the framework, methodologies, and applications of the human–machine collaborative creation in the metaverse era. Based on parallel theory, this article proposes a novel human–machine collaborative creation paradigm called ArtVerse, in which machines take on the roles of humans to perform creation exploration and evolution and build decentralized art organizations. Besides, the operational processes involving several key technologies are designed to achieve the proposed ArtVerse. Then, a prototype system of ArtVerse, our long-term efforts toward the human–machine collaborative painting, is presented. Finally, a new ecology of artistic creation in the metaverse era is demonstrated through the applications of the ArtVerse.
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Prior HCI literature has investigated design methodologies or strategies facilitating HAI interaction and dynamics in co-creative practices.
“Previous HCI literature has also investigated in design methodologies or strategies facilitating HAI interaction and dynamics in co-creative practices [32,33].”
Cites
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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High-Resolution Image Synthesis with Latent Diffusion Models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01042 · Cited by 15,880 · see citing works
On the Opportunities and Risks of Foundation Models
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High-Resolution Image Synthesis with Latent Diffusion Models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2021) · arXiv · doi:10.48550/arxiv.2112.10752 · Cited by 737 · see citing works
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Diffusion-Based Visual Art Creation: A Survey and New Perspectives
Wang, B., Chen, Q., & Wang, Z. (2025) · ACM Computing Surveys · doi:10.1145/3728459 · Cited by 40 · see citing works
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- Authors
- Guo, C., Dou, Y., Bai, T., Dai, X., Wang, C., & Wen, Y.
- Affiliations
- Chinese Academy of Sciences (CN)
- Macau University of Science and Technology (MO)
- National Museum of China (CN)
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Published
- 2023-04
- Volume
- 53
- Issue
- 4
- Pages
- 2200-2208
- ISSN
- 2168-2216 (ISSN-L)
- 2168-2232
- OpenAlex
- W4313485001
- Cited by
- 53
- References
- 5
- Citations by year
- 2026: 8 · 2025: 15 · 2024: 23 · 2023: 7
- FWCI
- 118.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Systems Man and Cybernetics Systems (publishedVersion)
- Funders
- Skywork Intelligence Culture and Technology LTD
- National Natural Science Foundation of China (61533019)
- Topics
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Generative Adversarial Networks and Image Synthesis
- Keywords
- human-machine collaboration, collaborative painting, metaverse, NFTs, foundation models, prototype system
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