Method and system for synthesizing three-dimensional data

A system for synthesizing three-dimensional (3D) data representing a plurality of possible scenarios from initial 3D data representing a given scenario, the system comprising:

• a data synthesis device comprising of at least one processor and a computer-readable medium storing instruction that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
• clustering initial 3D data to identify one or more regions of interest (ROIs), wherein the initial 3D data represent a given scenario;
• generating input specific noise data based on the one or more ROIs by an iterative process using Gaussian mixture model;
• and
• iteratively synthesizing 3D data based on the one or more ROIs and the input specific noise data using generative adversarial networks (GANs) to generate final synthesized 3D data, wherein the final synthesized 3D data represent a plurality of possible scenarios and are affine transforms of the initial 3D data.

A non-transitory computer-readable medium storing computer-executable instruction for:

• clustering initial 3D data to identify one or more regions of interest (ROIs), wherein the initial 3D data represent a given scenario;
• generating input specific noise data based on the one or more ROIs by an iterative process using Gaussian mixture model;
• and
• iteratively synthesizing 3D data based on the one or more ROIs and the input specific noise data using generative adversarial networks (GANs) to generate final synthesized 3D data, wherein the final synthesized 3D data represent a plurality of possible scenarios and are affine transforms of the initial 3D data.