Exploiting hierarchical structure learning with hyperbolic distance to enhance open world object detection

A computing device configured to perform open world object detection, the computing device including a processing device configured to execute instructions stored in memory to:

• receive object data, wherein the object data includes embeddings data corresponding to embeddings for known objects in a first input image;
• project the embeddings into a hyperbolic embedding space, wherein the hyperbolic embedding space includes embeddings in a plurality of categories of objects, and wherein each of the plurality of categories of objects includes one or more classes of objects;
• regularize the projected embeddings within the hyperbolic embedding space, wherein regularizing the projected embeddings within the hyperbolic embedding space includes determining respective hyperbolic averages of embeddings in each of the classes of objects determining a threshold distance based on the hyperbolic averages, and moving each of the projected embeddings (i) closer to embeddings in a same category of the plurality of categories and (ii) further away from embeddings in different categories of the plurality of categories;
• receive an unmatched query corresponding to an object in a second input image;
• and
• generate, in response to a determination that the unmatched query is less than the threshold distance from at least one of the hyperbolic averages, an output signal that indicates that the object in the second input image corresponds to an unknown object;
• and
• control an operation of a computer-controlled machine in response to the output signal.

A computer-controlled machine, comprising:

• at least one sensor configured to generate a first input image and a second input image;
• a control system configured to
• receive object data, wherein the object data includes embeddings data corresponding to embeddings for known objects in a first input image,
• project the embeddings into a hyperbolic embedding space, wherein the hyperbolic embedding space includes embeddings in a plurality of categories of objects, and wherein each of the plurality of categories of objects includes one or more classes of objects,
• regularize the projected embeddings within the hyperbolic embedding space, wherein regularizing the projected embeddings within the hyperbolic embedding space includes determining respective hyperbolic averages of embeddings in each of the classes of objects, determining a threshold distance based on the hyperbolic averages, and moving each of the projected embeddings (i) closer to embeddings in a same category of the plurality of categories and (ii) further away from embeddings in different categories of the plurality of categories,
• receive an unmatched query corresponding to an object in a second input image, and
• generate, in response to a determination that the unmatched query is less than the threshold distance from at least one of the hyperbolic averages, an output signal that indicates that the object in the second input image corresponds to an unknown object;
• and
• an actuator configured to control an operation of the computer-controlled machine in response to the output signal.