NVIDIA Corporation
NEURAL NETWORK TRAINING USING GROUND TRUTH DATA AUGMENTED WITH MAP INFORMATION FOR AUTONOMOUS MACHINE APPLICATIONS

Abstract:

In various examples, training sensor data generated by one or more sensors of autonomous machines may be localized to high definition (HD) map data to augment and/or generate ground truth data--e.g., automatically, in embodiments. The ground truth data may be associated with the training sensor data for training one or more deep neural networks (DNNs) to compute outputs corresponding to autonomous machine operations--such as object or feature detection, road feature detection and classification, wait condition identification and classification, etc. As a result, the HD map data may be leveraged during training such that the DNNs--in deployment--may aid autonomous machines in navigating environments safely without relying on HD map data to do so.