Distance to obstacle detection in autonomous machine applications

A method comprising:

• receiving first data representative of LIDAR information, second data representative of RADAR information, and third data representative of an image;
• receiving fourth data representative of a bounding shape corresponding to an object depicted in the image;
• correlating, with the bounding shape, depth information determined based at least in part on at least one of the LIDAR information or the RADAR information;
• generating ground truth data based at least in part on converting the depth information to a depth map by:
• determining a representative pixel within the bounding shape;
• selecting, from a shape within the bounding shape centered at the representative pixel, a subset of pixels of the bounding shape;
• and
• encoding, to each of the subset of pixels, a depth value of the depth values corresponding to the representative pixel;
• and
• training a neural network to compute a predicted depth map using the ground truth data.

A system comprising:

• an image sensor to generate first data representative of an image of an environment;
• a computing device including one or more processing devices and one or more memory devices communicatively coupled to the one or more processing devices and storing programmed instructions thereon that, when executed using the one or more processing devices, cause the instantiation of:
• a depth determiner to compute depth values using a neural network and based at least in part on the first data and second data representative of a distortion map generated to correspond to a field-of-view of the image sensor, the neural network trained using at least one of LIDAR data or RADAR data as ground truth;
• an object assigner to assign one or more of the depth values to one or more objects depicted in the image based at least in part on third data representative of one or more bounding shapes corresponding to the one or more objects;
• and
• a control component to perform one or more operations associated with control of the vehicle based at least in part on the one or more depth values and the third data.