CVDec 15, 2024

AURORA: Automated Unleash of 3D Room Outlines for VR Applications

arXiv:2412.11033v11 citationsh-index: 8VRCAI
Originality Synthesis-oriented
AI Analysis

This addresses the problem of automating VR scene creation for designers, but it appears incremental as it builds on existing techniques like image processing and 3D reconstruction.

The paper tackles the labor-intensive process of creating realistic VR scenes by proposing AURORA, a method that uses RGB-D images to automatically generate VR scenes, demonstrating effectiveness through experiments on self-captured and public datasets.

Creating realistic VR experiences is challenging due to the labor-intensive process of accurately replicating real-world details into virtual scenes, highlighting the need for automated methods that maintain spatial accuracy and provide design flexibility. In this paper, we propose AURORA, a novel method that leverages RGB-D images to automatically generate both purely virtual reality (VR) scenes and VR scenes combined with real-world elements. This approach can benefit designers by streamlining the process of converting real-world details into virtual scenes. AURORA integrates advanced techniques in image processing, segmentation, and 3D reconstruction to efficiently create realistic and detailed interior designs from real-world environments. The design of this integration ensures optimal performance and precision, addressing key challenges in automated indoor design generation by uniquely combining and leveraging the strengths of foundation models. We demonstrate the effectiveness of our approach through experiments, both on self-captured data and public datasets, showcasing its potential to enhance virtual reality (VR) applications by providing interior designs that conform to real-world positioning.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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