Training models to high-end performance requires availability of large
labeled datasets, which are expensive to get. The goal of our work is to
automatically synthesize labeled datasets that are relevant for a downstream
task. We propose Meta-Sim, which learns a generative model of synthetic scenes,
and obtain images as well as its corresponding ground-truth