Generating improved panoptic segmented digital images based on panoptic segmentation neural networks that utilize exemplar unknown object classes

A system comprising:

• one or more memory devices;
• and
• one or more processors configured to cause the system to:
• receive, via a client device, a panoptic segmentation request comprising a digital image portraying a plurality of objects;
• generate, from the digital image utilizing a panoptic segmentation neural network trained utilizing unknown object instance clusters to classify known object classes and unknown object classes, a panoptic segmented image comprising a semantic map of known labels assigned to a first set of objects and unknown labels assigned to a second set of objects for the plurality of objects;
• and
• provide, for display via the client device, the panoptic segmented image with the known labels and the unknown labels for the plurality of objects.

A non-transitory computer readable medium storing executable instructions which, when executed by a processing device, cause the processing device to perform operations comprising:

• receive, via a client device, a panoptic segmentation request comprising a digital image portraying a plurality of objects;
• generate, from the digital image utilizing a panoptic segmentation neural network trained utilizing unknown object instance clusters to classify known object classes and unknown object classes, a panoptic segmented image comprising a semantic map of known labels assigned to a first set of objects and unknown labels assigned to a second set of objects for the plurality of objects;
• and
• provide, for display via the client device, the panoptic segmented image with the known labels and the unknown labels for the plurality of objects.