3D Pano Inpainting: Building a VR Environment from a Single Input Panorama

Shivam Asija, Edward Du, Nam Nguyen, Stefanie Zollmann, Jonathan Ventura

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.