Patent ID: 11869149
Assignee: NVIDIA CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. One or more non-transitory computer readable media including instructions that, when executed by one or more processors, cause the one or more processors to train a machine learning model to generate representations of point clouds by performing the steps of:
executing a first neural network on a first point cloud that represents a first three-dimensional (3D) scene to generate a key set and a value set;
generating an output vector set based on a first query set, the key set, and the value set;
computing a plurality of spatial features based on the output vector set;
computing a plurality of quantized context features based on the output vector set and a first set of codes representing a first set of 3D geometry blocks; and
modifying the first neural network based on a likelihood of reconstructing the first point cloud, the plurality of quantized context features, and the plurality of spatial features to generate an updated neural network,
wherein a trained machine learning model includes the updated neural network, a second query set, and a second set of codes representing a second set of 3D geometry blocks and maps a point cloud representing a 3D scene to a representation of a plurality of 3D geometry instances.