AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2025

Casas, L.; Hannah, S.; Mitchell, K.

HoloJig: Interactive Spoken Prompt Specified Generative AI Environments Journal Article

In: IEEE Computer Graphics and Applications, vol. 45, no. 2, pp. 69–77, 2025, ISSN: 02721716 (ISSN).

Abstract | Links | BibTeX | Tags: 3-D rendering, Article, Collaborative workspace, customer experience, Economic and social effects, generative artificial intelligence, human, Immersive, Immersive environment, parallax, Real- time, simulation, Simulation training, speech, Time based, Virtual environments, Virtual Reality, Virtual reality experiences, Virtual spaces, VR systems

Mao, H.; Xu, Z.; Wei, S.; Quan, Y.; Deng, N.; Yang, X.

LLM-powered Gaussian Splatting in VR interactions Proceedings Article

In: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW, pp. 1654–1655, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833151484-6 (ISBN).

Abstract | Links | BibTeX | Tags: 3D Gaussian Splatting, 3D reconstruction, Content creation, Digital elevation model, Gaussians, High quality, Language Model, material analysis, Materials analysis, Physical simulation, Quality rendering, Rendering (computer graphics), Splatting, Virtual Reality, Volume Rendering, VR systems

@inproceedings{mao_llm-powered_2025,

title = {LLM-powered Gaussian Splatting in VR interactions},

author = {H. Mao and Z. Xu and S. Wei and Y. Quan and N. Deng and X. Yang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005148017&doi=10.1109%2fVRW66409.2025.00472&partnerID=40&md5=ee725f655a37251ff335ad2098d15f22},

doi = {10.1109/VRW66409.2025.00472},

isbn = {979-833151484-6 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},

pages = {1654–1655},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Recent advances in radiance field rendering, particularly 3D Gaussian Splatting (3DGS), have demonstrated significant potential for VR content creation, offering both high-quality rendering and an efficient production pipeline. However, current physics-based interaction systems for 3DGS are limited to either simplistic, unrealistic simulations or require substantial user input for complex scenes, largely due to the lack of scene comprehension. In this demonstration, we present a highly realistic interactive VR system powered by large language models (LLMs). After object-aware GS reconstruction, we prompt GPT-4o to analyze the physical properties of objects in the scene, which then guide physical simulations that adhere to real-world phenomena. Additionally, We design a GPT-assisted GS inpainting module to complete the areas occluded by manipulated objects. To facilitate rich interaction, we introduce a computationally efficient physical simulation framework through a PBD-based unified interpolation method, which supports various forms of physical interactions. In our research demonstrations, we reconstruct varieties of scenes enhanced by LLM's understanding, showcasing how our VR system can support complex, realistic interactions without additional manual design or annotation. © 2025 IEEE.},

keywords = {3D Gaussian Splatting, 3D reconstruction, Content creation, Digital elevation model, Gaussians, High quality, Language Model, material analysis, Materials analysis, Physical simulation, Quality rendering, Rendering (computer graphics), Splatting, Virtual Reality, Volume Rendering, VR systems},

pubstate = {published},

tppubtype = {inproceedings}

}