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3D Pano Inpainting: Building a VR Environment from a Single Input Panorama
Shivam Asija (California Polytechnic State University), Edward Du (California Polytechnic State University), Nam Nguyen (California Polytechnic State University), Stefanie Zollmann (University of Otago), Jonathan Ventura (California Polytechnic State University)
Abstract: Creating 360-degree 3D content is challenging because it requires either a multi-camera rig or a collection of many images taken from different perspectives. Our approach aims to generate a 360° VR scene from a single panoramic image using a learning-based inpainting method adapted for panoramic content. We introduce a pipeline capable of transforming an equirectangular panoramic RGB image into a complete 360° 3D virtual reality scene represented as a textured mesh, which is easily rendered on a VR headset using standard graphics rendering pipelines. We qualitatively evaluate our results on a synthetic dataset consisting of 360 panoramas in indoor scenes.