Depth estimation for monocular systems using adaptive ground truth weighting

An apparatus, comprising:

• a memory storing processor-readable code;
• and
• at least one processor coupled to the memory, the at least one processor configured to execute the processor-readable code to cause the at least one processor to perform operations including:
• receiving a predicted depth map and a measured depth map;
• determining a time difference between the predicted depth map and the measured depth map;
• determining, based on the time difference, a supervision loss term for the predicted depth map;
• and
• training a model based on the supervision loss term.

A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising:

• receiving a predicted depth map and a measured depth map;
• determining a time difference between the predicted depth map and the measured depth map;
• determining, based on the time difference, a supervision loss term for the predicted depth map;
• and
• training a model based on the supervision loss term.

A system comprising:

• an image sensor configured to capture image frames from a vehicle;
• a depth-sensing system configured to capture depth measurements from a vehicle;
• and
• a training system configured to:
• receive a measured depth map from the depth-sensing system and an image frame from the image sensor;
• determine a predicted depth map based on the image frame;
• determine a time difference between the predicted depth map and the measured depth map;
• determine, based on the time difference, a supervision loss term for the predicted depth map;
• and
• train a model based on the supervision loss term.