Generative AI for Immersive Video: Recent Advances and Future Opportunities
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Survey Track. Pages 10464-10472.
https://doi.org/10.24963/ijcai.2025/1162
Keywords
- Computer Vision: CV: Representation learning
- Computer Vision: CV: 3D computer vision
- Computer Vision: CV: Image and video synthesis and generation
- Multidisciplinary Topics and Applications: MTA: Interactive entertainment
Abstract
Immersive video serves as a key component of eXtended Reality (XR) that aims to create and interact with simulated virtual or hybrid environments. Such a technology allows users to experience immersive sensations that transcend time and space, and meanwhile continuously providing training data for emerging technologies like Embodied AI. Thanks to the advancements in sensing, computing, and display, recent years have witnessed many excellent works for XR and related hardware or software systems. However, challenges like high creation cost, lack of immersion, and limited scalability hinder the practical application of immersive video services. Whilst recently emerged generative artificial intelligence (GenAI) provides us with new insights in tackling existing challenges. In this paper, we conduct a comprehensive survey into the recent advances and future opportunities on how GenAI can benefit immersive video services. By introducing a systematic taxonomy, we meticulously classify the pertinent techniques and applications into three well-defined categories aligned with the pipeline of immersive video service: content creation, network delivery, and client-side display. This categorization enables a structured exploration of the diverse roles on how GenAI can benefit immersive video service, providing a framework for a more comprehensive understanding and evaluation of these technologies. To the best of our knowledge, this work is the first systematic survey of GenAI in XR settings, laying a foundation for future research in this interdisciplinary domain.
@inproceedings{ijcai2025p1162,
title = {Generative AI for Immersive Video: Recent Advances and Future Opportunities},
author = {Hu, Kaiyuan and Jin, Yili and Zhou, Hao and Du, Linfeng and Liu, Jiangchuan and Liu, Xue},
booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-25}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {James Kwok},
pages = {10464--10472},
year = {2025},
month = {8},
note = {Survey Track},
doi = {10.24963/ijcai.2025/1162},
url = {https://doi.org/10.24963/ijcai.2025/1162},
}
TY - CPAPER TI - Generative AI for Immersive Video: Recent Advances and Future Opportunities AU - Hu, Kaiyuan AU - Jin, Yili AU - Zhou, Hao AU - Du, Linfeng AU - Liu, Jiangchuan AU - Liu, Xue T2 - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2025 SP - 10464 EP - 10472 DO - 10.24963/ijcai.2025/1162 UR - https://doi.org/10.24963/ijcai.2025/1162 ER -Copied
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