Syb3r: A realistic synthetic benchmark for 3D reconstruction from images

Abstract

Benchmark datasets are the foundation of experimental evaluation in almost all vision problems. In the context of 3D reconstruction these datasets are rather difficult to produce. The field is mainly divided into datasets created from real photos with difficult experimental setups and simple synthetic datasets which are easy to produce, but lack many of the real world characteristics. In this work, we seek to find a middle ground by introducing a framework for the synthetic creation of realistic datasets and their ground truths. We show the benefits of such a purely synthetic approach over real world datasets and discuss its limitations.