Editable semantic map with virtual camera for mobile robot learning

Abstract

A computer-implemented method and system relate to computer vision. A first semantic map of an environment is three-dimensional (3D). A foreground scene and a background scene are generated individually using the semantic data of the first semantic map. The foreground scene contains foreground components of the first semantic map. The background scene contains background components of the first semantic map. A machine learning model generates an enhanced background view by completing incomplete regions of the background components. Input data is received to modify the background components, the foreground components, or both. A second semantic map is generated in 3D using the enhanced background view, the foreground components, and the input data. The second semantic map is 3D. Virtual camera data is generated using the second semantic map. The virtual camera data includes at least new image data and corresponding new depth data.

CPC Classifications