Unsupervised learning of scene structure for synthetic data generation

A system, comprising:

• at least one processor;
• and
• memory including instructions that, when executed by the at least one processor, cause the system to:
• generate a scene structure using at least a subset of a plurality of rules from a rule set, the plurality of rules specifying relationships between types of objects in a scene;
• determine one or more parameter values for one or more of the objects represented in the scene structure;
• generate a scene graph based on the scene structure and including the parameter values;
• and
• provide the scene graph to a rendering engine to render an image of the scene.

A method for synthesizing training data, comprising:

• obtaining a rule set including a plurality of rules specifying relationships between types of objects in a scene;
• generating a plurality of scene structures based on the plurality of rules;
• determining one or more parameter values for each of the objects represented in the plurality of scene structures;
• generating a plurality of scene graphs based on the plurality of scene structures and including the parameter values;
• and
• providing the plurality of scene graphs to a rendering engine to render a set of images including data for the objects represented in the images, the set of images representing training data for use in training one or more neural networks.