Publications

@inproceedings{leininger_understanding_2025,

title = {Understanding Creative Potential and Use Cases of AI-Generated Environments for Virtual Film Productions: Insights from Industry Professionals},

author = {P. Leininger and C. J. Weber and S. Rothe},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007976841&doi=10.1145%2f3706370.3727853&partnerID=40&md5=0d4cf7a2398d12d04e4f0ab182474a10},

doi = {10.1145/3706370.3727853},

isbn = {979-840071391-0 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {IMX - Proc. ACM Int. Conf. Interact. Media Experiences},

pages = {60–78},

publisher = {Association for Computing Machinery, Inc},

abstract = {Virtual production (VP) is transforming filmmaking by integrating real-time digital elements with live-action footage, offering new creative possibilities and streamlined workflows. While industry experts recognize AI's potential to revolutionize VP, its practical applications and value across different production phases and user groups remain underexplored. Building on initial research into generative and data-driven approaches, this paper presents the first systematic pilot study evaluating three types of AI-generated 3D environments - Depth Mesh, 360° Panoramic Meshes, and Gaussian Splatting - through the participation of 15 filmmaking professionals from diverse roles. Unlike commonly used 2D AI-generated visuals, our approach introduces navigable 3D environments that offer greater control and flexibility, aligning more closely with established VP workflows. Through expert interviews and literature research, we developed evaluation criteria to assess their usefulness beyond concept development, extending to previsualization, scene exploration, and interdisciplinary collaboration. Our findings indicate that different environments cater to distinct production needs, from early ideation to detailed visualization. Gaussian Splatting proved effective for high-fidelity previsualization, while 360° Panoramic Meshes excelled in rapid concept ideation. Despite their promise, challenges such as limited interactivity and customization highlight areas for improvement. Our prototype, EnVisualAIzer, built in Unreal Engine 5, provides an accessible platform for diverse filmmakers to engage with AI-generated environments, fostering a more inclusive production process. By lowering technical barriers, these environments have the potential to make advanced VP tools more widely available. This study offers valuable insights into the evolving role of AI in VP and sets the stage for future research and development. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.},

keywords = {3-D environments, 3D reconstruction, 3D Scene Reconstruction, 3d scenes reconstruction, AI-generated 3d environment, AI-Generated 3D Environments, Computer interaction, Creative Collaboration, Creatives, Digital content creation, Digital Content Creation., Filmmaking workflow, Filmmaking Workflows, Gaussian distribution, Gaussian Splatting, Gaussians, Generative AI, Graphical user interface, Graphical User Interface (GUI), Graphical user interfaces, Human computer interaction, human-computer interaction, Human-Computer Interaction (HCI), Immersive, Immersive Storytelling, Interactive computer graphics, Interactive computer systems, Interactive media, Mesh generation, Previsualization, Real-Time Rendering, Splatting, Three dimensional computer graphics, Virtual production, Virtual Production (VP), Virtual Reality, Work-flows},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{xing_immersed_2025,

title = {Immersed in my Ideas: Using Virtual Reality and LLMs to Visualize Users’ Ideas and Thoughts},

author = {Y. Xing and J. Ban and T. D. Hubbard and M. Villano and D. Gómez-Zará},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105001675169&doi=10.1145%2f3708557.3716330&partnerID=40&md5=20fb0623d2a1fff92282116b01fac4f3},

doi = {10.1145/3708557.3716330},

isbn = {979-840071409-2 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Int Conf Intell User Interfaces Proc IUI},

pages = {60–65},

publisher = {Association for Computing Machinery},

abstract = {We introduce the Voice Interactive Virtual Reality Annotation (VIVRA), an application that employs Large Language Models to facilitate brainstorming and idea exploration in an immersive 3D environment. As users think aloud to brainstorm and ideate, the application automatically detects, summarizes, suggests, and connects their ideas in real time. The experience brings participants into a room where their ideas emerge as interactive objects that embody the topics detected from their ideas. We evaluated the effectiveness of VIVRA in an exploratory study with 29 participants, followed by a user study with 10 participants comparing the application with other visualizations. Our results show that VIVRA helped participants reflect and think more about their ideas, serving as a valuable tool for personal exploration. We discuss the potential benefits and applications, highlighting the benefits of combining immersive 3D spaces and LLMs to explore, learn, and reflect on ideas. © 2025 Copyright held by the owner/author(s).},

keywords = {3-D environments, 3D modeling, Computer simulation languages, Creativity, Idea Generation, Immersive, Interactive virtual reality, Language Model, Large language model, Multimodal Interaction, Reflection, Text Visualization, Think aloud, Virtual environments, Virtual Reality, Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{wong_getwild_2022,

title = {GetWild: A VR Editing System with AI-Generated 3D Object and Terrain},

author = {S. M. Wong and C. -W. Chen and T. -Y. Pan and H. -K. Chu and M. -C. Hu},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151159899&doi=10.1145%2f3503161.3547733&partnerID=40&md5=668c107b586a77f7ef9bfde37d4dfb9f},

doi = {10.1145/3503161.3547733},

isbn = {978-145039203-7 (ISBN)},

year  = {2022},

date = {2022-01-01},

booktitle = {MM - Proc. ACM Int. Conf. Multimed.},

pages = {6988–6990},

publisher = {Association for Computing Machinery, Inc},

abstract = {3D environment artists typically use 2D screens and 3D modeling software to achieve their creation. However, creating 3D content using 2D tools is counterintuitive. Moreover, the process would be inefficient for junior artists in the absence of a reference. We develop a system called GetWild, which employs artificial intelligence (AI) models to generate the prototype of 3D objects/terrain and allows users to further edit the generated content in the virtual space. With the aid of AI, the user can capture an image to obtain a rough 3D object model, or start with drawing simple sketches representing the river, the mountain peak and the mountain ridge to create a 3D terrain prototype. Further, the virtual reality (VR) technique is used to provide an immersive design environment and intuitive interaction (such as painting, sculpturing, coloring, and transformation) for users to edit the generated prototypes. Compared with the existing 3D modeling software and systems, the proposed VR editing system with AI-generated 3D objects/terrain provides a more efficient way for the user to create virtual artwork. © 2022 Owner/Author.},

keywords = {3-D environments, 3-d terrains, 3D modeling, 3D models, 3D object, 3d-modeling, Editing systems, Landforms, Modeling softwares, Object generation, terrain generation, Terrain generations, Virtual Reality, Vr editing},

pubstate = {published},

tppubtype = {inproceedings}

}