Patent ID: 11948310
Assignee: TOYOTA RESEARCH INSTITUTE, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 13:
14. A method of jointly training a machine-learning-based monocular optical flow, depth, and scene flow estimator, the method comprising:
processing a pair of temporally adjacent monocular image frames using a first neural network structure to produce a first optical flow estimate;
processing the pair of temporally adjacent monocular image frames using a second neural network structure to produce an estimated depth map and an estimated scene flow;
processing the estimated depth map and the estimated scene flow using the second neural network structure to produce a second optical flow estimate; and
imposing a consistency loss between the first optical flow estimate and the second optical flow estimate that minimizes a difference between the first optical flow estimate and the second optical flow estimate to improve performance of the first neural network structure in estimating optical flow and the second neural network structure in estimating depth and scene flow.