Multi-task perception network with applications to scene understanding and advanced driver-assistance system

A computer program product for advanced driver-assistance, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising:

• extracting, from an input video stream comprising a plurality of images using a multi-task Convolutional Neural Network (CNN), shared features across different perception tasks, the different perception tasks comprising object detection and other perception tasks;
• concurrently solving, using the multi-task CNN, the different perception tasks in a single pass by concurrently processing corresponding ones of the shared features by respective different branches of the multi-task CNN to provide a plurality of different perception task outputs, each of the respective different branches corresponding to a respective one of the different perception tasks;
• forming a parametric representation of a driving scene as at least one top-view map responsive to the plurality of different perception task outputs;
• and
• controlling an operation of the vehicle for collision avoidance responsive to the at least one top-view map indicating an impending collision.

A computer processing system for advanced driver-assistance, comprising:

• a memory device including program code stored thereon;
• a hardware processor, operatively coupled to the memory device, and configured to run the program code stored on the memory device to
• extract, from an input video stream comprising a plurality of images using a multi-task Convolutional Neural Network (CNN), shared features across different perception tasks, the different perception tasks comprising object detection and other perception tasks;
• concurrently solve, using the multi-task CNN, the different perception tasks in a single pass by concurrently processing corresponding ones of the shared features by respective different branches of the multi-task CNN to provide a plurality of different perception task outputs, each of the respective different branches corresponding to a respective one of the different perception tasks;
• form a parametric representation of a driving scene as at least one top-view map responsive to the plurality of different perception task outputs;
• and
• control an operation of the vehicle for collision avoidance responsive to the at least one top-view map indicating an impending collision.