Systems and methods for three-dimensional object detection are disclosed herein. One embodiment inputs, to a neural network, a two-dimensional label associated with an object to produce a Normalized-Object-Coordinate-Space (NOCS) image and a shape vector, the shape vector mapping to a continuously traversable coordinate shape space (CSS); decodes the NOCS image and the shape vector to an object model in the CSS; back-projects, in a frustum, the NOCS image to a LIDAR point cloud; identifies correspondences between the LIDAR point cloud and the object model to estimate an affine transformation between the LIDAR point cloud and the object model; iteratively refines the affine transformation using a differentiable SDF renderer; extracts automatically a three-dimensional label for the object based, at least in part, on the iteratively refined affine transformation; and performs three-dimensional object detection of the object based, at least in part, on the extracted three-dimensional label for the object.
SYSTEMS AND METHODS FOR 3D OBJECT DETECTION