Automated Scene Flow Data Generation for Training and Verification
This addresses the data scarcity problem for training and verification in autonomous driving, but it is incremental as it builds on existing synthetic data generation methods.
The paper tackles the lack of ground truth data for scene flow algorithms in autonomous driving by demonstrating a technology to generate synthetic data with dense and precise scene flow ground truth.
Scene flow describes the 3D position as well as the 3D motion of each pixel in an image. Such algorithms are the basis for many state-of-the-art autonomous or automated driving functions. For verification and training large amounts of ground truth data is required, which is not available for real data. In this paper, we demonstrate a technology to create synthetic data with dense and precise scene flow ground truth.