Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for estimating the three-dimensional geometry of an object in a digital image by modeling the ground, object, and camera simultaneously. In particular, in one or more embodiments, the disclosed systems receive a two-dimensional digital image portraying an object. Further, the systems generate, utilizing a dense representation neural network, an estimate of an object-ground relationship of the object portrayed in the two-dimensional digital image and an estimate of camera parameters for the two-dimensional digital image. Additionally, the systems generate, utilizing a perspective field guided pixel height reprojection model, one or more of a three-dimensional point cloud or a depth map of the object from the estimated object-ground relationship and the estimated camera parameters.

Abstract: A method of generating virtual sensor data of a virtual single-photon avalanche diode (SPAD) lidar sensor includes generating a two-dimensional (2D) lidar array having a plurality of cells. The method further includes interpolating image data from a virtual camera with the 2D lidar array to define auxiliary image data, generating a virtual ambient image based on a red-channel (R-channel) data of the auxiliary image data, identifying a plurality of virtual echoes of the virtual SPAD lidar sensor based on the R-channel data and a defined photon threshold, defining a virtual point cloud indicative of virtual photon measurements of the virtual SPAD lidar sensor based on the plurality of virtual echoes, and outputting data indicative of the virtual ambient image, the virtual photon measurements, the virtual point cloud, or a combination thereof, as the virtual sensor data of the virtual SPAD lidar sensor.

Abstract: In one embodiment, a method includes receiving sensor data. The sensor data is based on information from a first set of echo points and a second set of echo points. At least one echo point from the first set of echo points and one echo point from the second set of echo points originate from a single beam. The method includes generating a first set of feature maps based on the first set of echo points and a second set of feature maps based on the second set of echo points. The method includes predicting a bounding box for the object based on the first set of feature maps and the second set of feature maps.

Abstract: Systems, methods, and other embodiments described herein relate to generating bounding box proposals. In one embodiment, a method includes generating blended 2-dimensional (2D) data based on 2D data and 3-dimensional (3D) data, and generating blended 3D data based on the 2D data and the 3D data. The method includes generating 2D features based on the 2D data and the blended 2D data, generating 3D features based on the 3D data and the blended 3D data, and generating the bounding box proposals based on the 2D features and the 3D features.