The Metaverse presents an emerging creative expression and collaboration frontier where generative artificial intelligence (GenAI) can play a pivotal role with its ability to generate multimodal content from simple pr...
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The Metaverse presents an emerging creative expression and collaboration frontier where generative artificial intelligence (GenAI) can play a pivotal role with its ability to generate multimodal content from simple prompts. These prompts allow the metaverse to interact with GenAI, where context information, instructions, input data, or even output indications constituting the prompt can come from within the metaverse. However, their integration poses challenges regarding interoperability, lack of standards, scalability, and maintaining a high-quality user experience. This paper explores how GenAI can productively assist in enhancing creativity within the contexts of the Metaverse and unlock new opportunities. We provide a technical, in-depth overview of the different generative models for image, video, audio, and 3D content within the Metaverse environments. We also explore the bottlenecks, opportunities, and innovative applications of GenAI from the perspectives of end users, developers, service providers, and AI researchers. This survey commences by highlighting the potential of GenAI for enhancing the Metaverse experience through dynamic content generation to populate massive virtual worlds. Subsequently, we shed light on the ongoing research practices and trends in multimodal content generation, enhancing realism and creativity and alleviating bottlenecks related to standardization, computational cost, privacy, and safety. Lastly, we share insights into promising research directions toward the integration of GenAI with the Metaverse for creative enhancement, improved immersion, and innovative interactive applications.
This book and its companion volume, LNCS vols. 7928 and 7929 constitute the proceedings of the 4th International Conference on Swarm intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised full pa...
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ISBN:
(数字)9783642387036
ISBN:
(纸本)9783642387029
This book and its companion volume, LNCS vols. 7928 and 7929 constitute the proceedings of the 4th International Conference on Swarm intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised full papers presented were carefully reviewed and selected from 268 submissions. The papers are organized in 22 cohesive sections covering all major topics of swarm intelligence research and developments. The following topics are covered in this volume: analysis of swarm intelligence based algorithms, particle swarm optimization, applications of particle swarm optimization algorithms, ant colony optimization algorithms, biogeography-based optimization algorithms, novel swarm-based search methods, bee colony algorithms, differential evolution, neural networks, fuzzy methods, evolutionary programming and evolutionary games.
The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm intelligence, ICSI 2011, held in Chongqing, China, in June 2011.The 143 revised full papers present...
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ISBN:
(数字)9783642215155
ISBN:
(纸本)9783642215148
The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm intelligence, ICSI 2011, held in Chongqing, China, in June 2011.
The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.
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