Generating ground truths for machine learning

Abstract

A messaging system processes three-dimensional (3D) models to generate ground truths for training machine learning models for applications of the messaging system. A method of generating ground truths for machine learning includes generating a plurality of first rendered images from a first 3D base model where each first rendered image includes the 3D base model modified by first augmentations of a plurality of augmentations. The method further includes determining for a second 3D base model incompatible augmentations of the first plurality of augmentations, where the incompatible augmentations indicate changes to fixed features of the second 3D base model, and generating a plurality of second rendered images from a second 3D base model, each second rendered image comprising the second 3D base model modified by second augmentations, the second augmentations corresponding to the first augmentations of a corresponding first rendered image, where the second augmentations comprises augmentations of the first augmentations that are not incompatible augmentations.