AHCI RESEARCH GROUP
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OUR RESEARCH
Scientific Publications
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2024
Numan, N.; Rajaram, S.; Kumaravel, B. T.; Marquardt, N.; Wilson, A. D.
SpaceBlender: Creating Context-Rich Collaborative Spaces Through Generative 3D Scene Blending Proceedings Article
In: UIST - Proc. Annual ACM Symp. User Interface Softw. Technol., Association for Computing Machinery, Inc, 2024, ISBN: 979-840070628-8 (ISBN).
Abstract | Links | BibTeX | Tags: 3D modeling, 3D scenes, 3D spaces, AI techniques, Artificial environments, Collaborative spaces, Collaborative tasks, Generative adversarial networks, Generative AI, Telepresence, Virtual environments, Virtual Reality, Virtual reality telepresence, Virtual spaces, VR telepresence
@inproceedings{numan_spaceblender_2024,
title = {SpaceBlender: Creating Context-Rich Collaborative Spaces Through Generative 3D Scene Blending},
author = {N. Numan and S. Rajaram and B. T. Kumaravel and N. Marquardt and A. D. Wilson},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209252034&doi=10.1145%2f3654777.3676361&partnerID=40&md5=8744057832f9098eabfd16c8b2b5fe62},
doi = {10.1145/3654777.3676361},
isbn = {979-840070628-8 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {UIST - Proc. Annual ACM Symp. User Interface Softw. Technol.},
publisher = {Association for Computing Machinery, Inc},
abstract = {There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR) applications. However, today's models produce artificial environments, falling short of supporting collaborative tasks that benefit from incorporating the user's physical context. To generate environments that support VR telepresence, we introduce SpaceBlender, a novel pipeline that utilizes generative AI techniques to blend users' physical surroundings into unified virtual spaces. This pipeline transforms user-provided 2D images into context-rich 3D environments through an iterative process consisting of depth estimation, mesh alignment, and diffusion-based space completion guided by geometric priors and adaptive text prompts. In a preliminary within-subjects study, where 20 participants performed a collaborative VR affinity diagramming task in pairs, we compared SpaceBlender with a generic virtual environment and a state-of-the-art scene generation framework, evaluating its ability to create virtual spaces suitable for collaboration. Participants appreciated the enhanced familiarity and context provided by SpaceBlender but also noted complexities in the generative environments that could detract from task focus. Drawing on participant feedback, we propose directions for improving the pipeline and discuss the value and design of blended spaces for different scenarios. © 2024 ACM.},
keywords = {3D modeling, 3D scenes, 3D spaces, AI techniques, Artificial environments, Collaborative spaces, Collaborative tasks, Generative adversarial networks, Generative AI, Telepresence, Virtual environments, Virtual Reality, Virtual reality telepresence, Virtual spaces, VR telepresence},
pubstate = {published},
tppubtype = {inproceedings}
}
There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR) applications. However, today's models produce artificial environments, falling short of supporting collaborative tasks that benefit from incorporating the user's physical context. To generate environments that support VR telepresence, we introduce SpaceBlender, a novel pipeline that utilizes generative AI techniques to blend users' physical surroundings into unified virtual spaces. This pipeline transforms user-provided 2D images into context-rich 3D environments through an iterative process consisting of depth estimation, mesh alignment, and diffusion-based space completion guided by geometric priors and adaptive text prompts. In a preliminary within-subjects study, where 20 participants performed a collaborative VR affinity diagramming task in pairs, we compared SpaceBlender with a generic virtual environment and a state-of-the-art scene generation framework, evaluating its ability to create virtual spaces suitable for collaboration. Participants appreciated the enhanced familiarity and context provided by SpaceBlender but also noted complexities in the generative environments that could detract from task focus. Drawing on participant feedback, we propose directions for improving the pipeline and discuss the value and design of blended spaces for different scenarios. © 2024 ACM.