SpaceBlender: Creating Context-Rich Collaborative Spaces Through
  Generative 3D Scene Blending
Authors: name: Nels Numan, name: Shwetha Rajaram, name: Balasaravanan Thoravi Kumaravel, name: Nicolai Marquardt, name: Andrew D. Wilson

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.