Multi-View Image-Based 3D Reconstruction in Indoor Scenes: A Survey

Abstract: Three-dimensional reconstruction technology plays an important role in indoor scenes by converting objects and structures in indoor environments into accurate 3D models using multi-view RGB images. It offers a wide range of applications in fields such as virtual reality, augmented reality, indoor navigation, and game development. Existing methods based on multi-view RGB images have made significant progress in 3D reconstruction. These image-based reconstruction methods not only possess good expressive power and generalization performance, but also handle complex geometric shapes and textures effectively. Despite facing challenges such as lighting variations, occlusion, and texture loss in indoor scenes, these challenges can be effectively addressed through deep neural networks, neural implicit surface representations, and other techniques. The technology of indoor 3D reconstruction based on multi-view RGB images has a promising future. It not only provides immersive and interactive virtual experiences but also brings convenience and innovation to indoor navigation, interior design, and virtual tours. As the technology evolves, these image-based reconstruction methods will be further improved to provide higher quality and more accurate solutions for indoor scene reconstruction.

Keywords: 3D reconstruction; MVS; NeRF; Neural implicit surface