Indoor Panorama

Indoor panorama research focuses on creating accurate and detailed 3D models and semantic understanding of indoor spaces from single or multiple 360° images. Current efforts concentrate on developing novel view synthesis techniques, often employing deep learning architectures like transformers and Gaussian splatting, to generate realistic novel views and improve inpainting capabilities for tasks such as furniture removal and scene editing. These advancements are significant for applications in virtual home staging, robotics, and scene understanding, providing richer and more complete representations of indoor environments than traditional methods.