Deep learning based 3D reconstruction of indoor scenes

Abstract

Recent advancement in deep learning techniques has opened doors for wide variety of applications. With growing interests in deep learning and geometry, lots of computer vision problems have been tackled using deep learning. In this work, we try to create a framework for a learning based 3D reconstruction of interiors of building from multiple 2D images that capture the entire scene of interest. We use PoseNet for regressing over the camera pose to establish spatial relationship between constituents of a scene. This work is a step towards solving a bigger problem of reconstruction from incomplete data of the scene.