MACHINE-LEARNING FOR 3D OBJECT DETECTION

    公开(公告)号:US20220189070A1

    公开(公告)日:2022-06-16

    申请号:US17553403

    申请日:2021-12-16

    Abstract: A computer-implemented method of machine-learning for learning a neural network that encodes a super-point of a 3D point cloud into a latent vector. The method including obtaining a dataset of super-points. Each super-point is a set of points of a 3D point cloud. The set of points represents at least a part of an object. The method further includes learning the neural network based on the dataset of super-points. The learning includes minimizing a loss. The loss penalizes a disparity between two super-points. This constitutes improved machine-learning for 3D object detection.

Patent Agency Ranking