AURORA generates virtual and hybrid outlines from RGB-D images, offering fully modeled CAD scenes or hybrid scenes that combine Gaussian Splatting with CAD models.
top left: input images; top right: novel view synthesis results using Gaussian Splatting
bottom left: : fully modelled scenes; bottom right: the scene overview with camera locations
top left: input images; top right: novel view synthesis results using Gaussian Splatting
bottom left: : hybrid scenes with CAD and GS; bottom right: the scene overview with camera locations
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.
To explore novel views of the scene, we interpolate the camera poses and incorporate fixed-location movements, including vertical (up and down) and horizontal (left and right) shifts.
This video demonstrates the fully modeled scene generated from a sequence of 200 input images.
@inproceedings{han2024aurora,
author = {Han, Huijun and Liang, Yongqing and Zhou, Yuanlong and Wang, Wenping and Rojas-Muñoz, Edgar J. and Li, Xin},
title = {AURORA: Automated Unleash of 3D Room Outlines for VR Applications},
booktitle = {Proceedings of the 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry (VRCAI '24)},
year = {2024},
date = {December 1--2, 2024},
location = {Nanjing, China},
publisher = {ACM},
address = {New York, NY, USA},
pages = {8},
url = {https://doi.org/10.1145/3703619.3706036},
doi = {10.1145/3703619.3706036}
}