Special Issue on Multi-Modal Content Generation for Games

Aim and Scope

Multi-modal content generation aims to generate realistic data across various modalities, including text, speech, music, images, video, 3D meshes & point clouds, etc. This technology holds significant potential to transform modern game design and content creation. By automating the production of diverse, high-quality assets, it can profoundly enhance player experiences while accelerating the game development cycle. The main focus of this special issue will be on exploring new learning theories, methods, tools, datasets, and metrics specifically for generating and evaluating high-quality and realistic game content. This includes elements such as scripts, background music, characters, 3D scenes, rigging, narritive, and more. This special issue aims to provide a platform for fostering interdisciplinary research and sharing the latest developments in generative artificial intelligence, particularly focusing on multi-modal and cross-modal generative models, as applied to the games field.

The scope of this special issue includes, but is not limited to, the following areas:

Datasets or simulators designed for multi-modal content generation and / or evaluation, with potential applications in games.
Tools for creating and evaluating multi-modal game content.
Quantitative and qualitative methods for evaluating multi-modal game content, including joint evaluation approaches.
Multi-modal or cross-modal content generation methods specifically tailored for games.
Few-shot and zero-shot learning algorithms applicable to multi-modal game content generation.
Methods for evaluating and improving game facet orchestration.
Methods for generating game worlds that incorporate multi-modal data and multifaceted content.
Large Language Models for generating multi-modal game content.
Applications of the aforementioned methods and tools within the game industry.

Important Dates:

Paper submission: December 31, 2025
Completion of first round of review: January 31, 2026
Completion of final review: March 31, 2026
Submission of final manuscripts: April 30, 2026
Scheduled Publication: June, 2026

Submission Instructions:

Read the Information for Authors at https://cis.ieee.org/publications/t-games
Submit your manuscript at the IEEE TG webpage (https://mc.manuscriptcentral.com/tg-ieee) and follow the submission procedure. Please, clearly indicate on the first page of the manuscript and in the cover letter that the manuscript is submitted to this Special Issue. Early submissions are welcome. We will start the review process as soon as we receive your contributions.

Potential Authors:

Potential authors include but not limited to researchers and students in the following institutes/univerisities:

Center for Design / Khoury College of Computer Sciences, Northeastern University
Computer Graphics and Visualization Group, Delft University of Technology
Game Innovation Lab, New York University
Game AI Group, Queen Mary University of London
Institue of Digital Games, Univerisity of Malta
Centre for Vision, Speech and Signal Processing, University of Surrey
Zhejiang University
Shanghai Jiaotong University
Sichuan University
IT University of Copenhagen
modl.ai
Ritsumeikan University
University of Alberta

Guest Editors:

Zhenhua Feng

Jiangnan University, Wuxi, China
Email: fengzhenhua@jiangnan.edu.cn
Zhenhua Feng (IEEE Senior Member) is a Professor of machine learning and computer vision at the School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China. He received the Ph.D. degree from the Centre for Vision, Speech and Signal Processing, University of Surrey, UK, in 2016. Then he worked as Research Fellow, Senior Research Fellow, Lecturer, and Senior Lecturer at the University of Surrey from 2016 to 2024. His research interests include computer vision, machine learning, and artificial intelligence. He has published more than 100 scientific papers in top-tier conferences and journals, such as IEEE TPAMI, IJCV, CVPR, ICCV, ECCV, AAAI, NeurIPS, ACL, IEEE TIP, IEEE TNNLS, IEEE TIFS, etc. He received the 2024 ICPR Best Scientific Paper Award, the 2017 European Biometrics Industry Award from the European Association for Biometrics (EAB), the AMDO 2018 Best Paper Award for Commercial Applications, etc. He currently serves as an Associate Editor for IEEE TNNLS and Complex & Intelligent Systems. He also served as the Guest Editor for IJCV (2023), Program Chair for BMVC 2022, Area Chair for BMVC 2021/22/23/24/25 and CVMP 2022/23, and Senior Program Committee Member for IJCAI 2021.

Jialin Liu

Lingnan University, Hong Kong SAR, China
Email: jialin.liu@ln.edu.hk
Jialin Liu is an Associate Professor in the School of Data Science at the Lingnan University, Hong Kong SAR, China. She received her PhD in 2016 from Université Paris-Saclay, France, MSc in 2013 from École Polytechnique and Université Paris-Sud, France, Diplôme d'Ingénieur in 2012 from Polytech'Paris-Sud, France, and BSc in 2010 from Huazhong University of Science and Technology, China. Her main research interests include game AI, evolutionary computation, and fair machine learning. She is an Associate Editor of the IEEE Transactions on Games, IEEE Transactions on Evolutionary Computation, IEEE Transactions on Artificial Intelligence and Knowledge-Based Systems.

Ahmed Khalifa

Institute of Digital Games, University of Malta, Malta
Email: ahmed.khalifa@um.edu.mt
Ahmed Khalifa is an AI researcher/lecturer at the Institute of Digital Games, University of Malta. He got his PhD from New York University back in 2020. He has published more than 60 papers between workshops, conferences, and journals. His work focused on exploring different methods and techniques for generating game content. He is known for his research on PCGRL, PCG with Quality Diversity, and Deep Tingle. He is also an independent game designer/developer with more than 40 released games/prototypes. Some of his games were nominated for multiple awards in different conferences such IndiePrize, Melbourne Queer Games Festival, Queer Games Conference, and International Mobile Game Awards.

Huanhuan Chen

University of Science and Technology of China, Hefei, China
Email: hchen@ustc.edu.cn
Huanhuan Chen (IEEE Fellow), is a professor in School of Computer Science, University of Science & Technology of China (USTC), Hefei, China. He received the B.Sc. degree from USTC, Hefei, China, in 2004, and Ph.D. degree, sponsored by Dorothy Hodgkin Postgraduate Award, in computer science at the University of Birmingham, Birmingham, UK, in 2008. He worked in University of Birmingham and University of Leeds in the UK from 2008 to 2012, respectively. His PhD thesis "Diversity and Regularization in Neural Network Ensembles" has received 2011 IEEE Computational Intelligence Society Outstanding PhD Dissertation award (the only winner) and 2009 CPHC/British Computer Society Distinguished Dissertations Award (the runner up). His work “Probabilistic Classification Vector Machines” on Bayesian machine learning published in IEEE Transactions on Neural Networks, has been awarded as IEEE Transactions on Neural Networks Outstanding 2009 Paper Award (bestowed in 2012, and only one paper in 2009 receive this award). In 2015, Dr. Chen received the International Neural Network Society (INNS) Young Investigator Award in 2015 for his significant contributions in the field of Neural Networks. His research interests include computational intelligence, statistical machine learning, data fusion, neural networks, Bayesian inference and evolutionary computation, etc.

Josef Kittler

University of Surrey, Guildford, UK
Email: j.kittler@surrey.ac.uk
Josef Kittler (IEEE Life Member, FREng) received the B.A., Ph.D., and D.Sc. degrees from the University of Cambridge in 1971, 1974, and 1991, respectively. He is a Distinguished Professor of machine intelligence with the Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, U.K. He has published the textbook Pattern Recognition: A Statistical Approach and more than 1000 scientific articles. His publications have been cited by 78,000+ times. His research interests include biometrics, video and image database retrieval, medical image analysis, and cognitive vision. He served as a member of the Editorial Board for the IEEE Transactions on Patttern Analysis and Machine Intelligence from 1982 to 1985. He served as the President of the Inetrnational Association for Pattern Recognition from 1994 to 1996. He was a Series Editor of Springer Lecture Notes in Computer Science 2004-2016. Currently he serves on the editorial boards of Pattern Recognition, Pattern Recognition Letters, and Springer Nature Computer Science.