AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2024
Yin, Z.; Wang, Y.; Papatheodorou, T.; Hui, P.
Text2VRScene: Exploring the Framework of Automated Text-driven Generation System for VR Experience Proceedings Article
In: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces, VR, pp. 701–711, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835037402-5 (ISBN).
Abstract | Links | BibTeX | Tags: Automated systems, Automation, Digital contents, Generation systems, Generative model, Human computer interaction, Human computer interaction (HCI), Human-centered computing, Interaction paradigm, Interaction paradigms, Interaction techniques, Language Model, Natural language processing systems, Text input, User interfaces, Virtual Reality
@inproceedings{yin_text2vrscene_2024,
title = {Text2VRScene: Exploring the Framework of Automated Text-driven Generation System for VR Experience},
author = {Z. Yin and Y. Wang and T. Papatheodorou and P. Hui},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191431035&doi=10.1109%2fVR58804.2024.00090&partnerID=40&md5=5484a5bc3939d003efe68308f56b15a6},
doi = {10.1109/VR58804.2024.00090},
isbn = {979-835037402-5 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces, VR},
pages = {701–711},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {With the recent development of the Virtual Reality (VR) industry, the increasing number of VR users pushes the demand for the massive production of immersive and expressive VR scenes in related industries. However, creating expressive VR scenes involves the reasonable organization of various digital content to express a coherent and logical theme, which is time-consuming and labor-intensive. In recent years, Large Language Models (LLMs) such as ChatGPT 3.5 and generative models such as stable diffusion have emerged as powerful tools for comprehending natural language and generating digital contents such as text, code, images, and 3D objects. In this paper, we have explored how we can generate VR scenes from text by incorporating LLMs and various generative models into an automated system. To achieve this, we first identify the possible limitations of LLMs for an automated system and propose a systematic framework to mitigate them. Subsequently, we developed Text2VRScene, a VR scene generation system, based on our proposed framework with well-designed prompts. To validate the effectiveness of our proposed framework and the designed prompts, we carry out a series of test cases. The results show that the proposed framework contributes to improving the reliability of the system and the quality of the generated VR scenes. The results also illustrate the promising performance of the Text2VRScene in generating satisfying VR scenes with a clear theme regularized by our well-designed prompts. This paper ends with a discussion about the limitations of the current system and the potential of developing similar generation systems based on our framework. © 2024 IEEE.},
keywords = {Automated systems, Automation, Digital contents, Generation systems, Generative model, Human computer interaction, Human computer interaction (HCI), Human-centered computing, Interaction paradigm, Interaction paradigms, Interaction techniques, Language Model, Natural language processing systems, Text input, User interfaces, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
With the recent development of the Virtual Reality (VR) industry, the increasing number of VR users pushes the demand for the massive production of immersive and expressive VR scenes in related industries. However, creating expressive VR scenes involves the reasonable organization of various digital content to express a coherent and logical theme, which is time-consuming and labor-intensive. In recent years, Large Language Models (LLMs) such as ChatGPT 3.5 and generative models such as stable diffusion have emerged as powerful tools for comprehending natural language and generating digital contents such as text, code, images, and 3D objects. In this paper, we have explored how we can generate VR scenes from text by incorporating LLMs and various generative models into an automated system. To achieve this, we first identify the possible limitations of LLMs for an automated system and propose a systematic framework to mitigate them. Subsequently, we developed Text2VRScene, a VR scene generation system, based on our proposed framework with well-designed prompts. To validate the effectiveness of our proposed framework and the designed prompts, we carry out a series of test cases. The results show that the proposed framework contributes to improving the reliability of the system and the quality of the generated VR scenes. The results also illustrate the promising performance of the Text2VRScene in generating satisfying VR scenes with a clear theme regularized by our well-designed prompts. This paper ends with a discussion about the limitations of the current system and the potential of developing similar generation systems based on our framework. © 2024 IEEE.
Lin, Y.; Gao, Z.; Du, H.; Niyato, D.; Kang, J.; Xiong, Z.; Zheng, Z.
Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse Journal Article
In: IEEE Transactions on Services Computing, vol. 17, no. 5, pp. 2067–2079, 2024, ISSN: 19391374 (ISSN).
Abstract | Links | BibTeX | Tags: AI-generated content, Block-chain, Blockchain, Computational modelling, Content services, Data Mining, Digital contents, Information Management, Metaverse, Metaverses, Resource management, Semantic communication, Semantics, Virtual Reality
@article{lin_blockchain-based_2024,
title = {Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse},
author = {Y. Lin and Z. Gao and H. Du and D. Niyato and J. Kang and Z. Xiong and Z. Zheng},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189177655&doi=10.1109%2fTSC.2024.3382958&partnerID=40&md5=5e3e80fbc88a49293b892acd762af3e9},
doi = {10.1109/TSC.2024.3382958},
issn = {19391374 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Transactions on Services Computing},
volume = {17},
number = {5},
pages = {2067–2079},
abstract = {AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms. © 2008-2012 IEEE.},
keywords = {AI-generated content, Block-chain, Blockchain, Computational modelling, Content services, Data Mining, Digital contents, Information Management, Metaverse, Metaverses, Resource management, Semantic communication, Semantics, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms. © 2008-2012 IEEE.
2023
Lin, Y.; Gao, Z.; Du, H.; Niyato, D.
Blockchain-Aided AI-Generated Content Services: Stackelberg Game-Based Content Caching Approach Proceedings Article
In: C., Ardagna; B., Benatallah; H., Bian; C.K., Chang; R.N., Chang; J., Fan; G.C., Fox; Z., Jin; X., Liu; H., Ludwig; M., Sheng; J., Yang (Ed.): Proc. - IEEE Int. Conf. Web Serv., ICWS, pp. 186–195, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835030485-5 (ISBN).
Abstract | Links | BibTeX | Tags: AI-generated content, Block-chain, Blockchain, Caching mechanism, Content caching, Content services, Digital contents, Game-Based, Metaverse, Metaverses, Shared virtual environments, Stackelberg Games, Virtual Reality
@inproceedings{lin_blockchain-aided_2023,
title = {Blockchain-Aided AI-Generated Content Services: Stackelberg Game-Based Content Caching Approach},
author = {Y. Lin and Z. Gao and H. Du and D. Niyato},
editor = {Ardagna C. and Benatallah B. and Bian H. and Chang C.K. and Chang R.N. and Fan J. and Fox G.C. and Jin Z. and Liu X. and Ludwig H. and Sheng M. and Yang J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173901801&doi=10.1109%2fICWS60048.2023.00038&partnerID=40&md5=3a323f44b98bd9e7a86a22523efcd488},
doi = {10.1109/ICWS60048.2023.00038},
isbn = {979-835030485-5 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {Proc. - IEEE Int. Conf. Web Serv., ICWS},
pages = {186–195},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. AIGC services can offer personalized content with user assistance, making the Metaverse more human-centric. However, it is difficult for participants to exchange data and construct trust among unknown Metaverse participants. To address the above challenge, we propose an integration of blockchain and AIGC to construct decentralized trust among participants. We design a smart contract-based verification mechanism to prevent random outcomes of AIGC services and guarantee the authenticity of digital contents. Given the quality of digital contents provided by the previous mechanisms, we then utilize them as metrics to establish a Stackelberg game-based content caching mechanism to maximize Metaverse participants' profits. Simulation results show that the proposed caching mechanism can improve utility by 30% compared to other mechanisms. © 2023 IEEE.},
keywords = {AI-generated content, Block-chain, Blockchain, Caching mechanism, Content caching, Content services, Digital contents, Game-Based, Metaverse, Metaverses, Shared virtual environments, Stackelberg Games, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. AIGC services can offer personalized content with user assistance, making the Metaverse more human-centric. However, it is difficult for participants to exchange data and construct trust among unknown Metaverse participants. To address the above challenge, we propose an integration of blockchain and AIGC to construct decentralized trust among participants. We design a smart contract-based verification mechanism to prevent random outcomes of AIGC services and guarantee the authenticity of digital contents. Given the quality of digital contents provided by the previous mechanisms, we then utilize them as metrics to establish a Stackelberg game-based content caching mechanism to maximize Metaverse participants' profits. Simulation results show that the proposed caching mechanism can improve utility by 30% compared to other mechanisms. © 2023 IEEE.