Object subpart-guided filtering for object detection

A device, comprising processing circuitry configured to:

• obtain, from one or more artificial neural network (ANN) entities trained to localize objects and one or more subparts of such objects in images, a plurality of object proposals and one or more subpart proposals in a same image;
• perform a first filtering of the object proposals;
• for each subpart proposal, match the subpart proposal with a corresponding one of the object proposals remaining after the first filtering, and
• perform a second filtering of the object proposals remaining after the first filtering and not matched with any of the one or more subpart proposals,
• wherein the first filtering and the second filtering are based on classification confidence scores and proximity scores of the object proposals, and wherein the second filtering is statistically more aggressive than the first filtering.

A computer program comprising computer code that, when run on processing circuitry of a device, causes the device to:

• obtain, from one or more artificial neural network (ANN) entities trained to localize objects and one or more subparts of such objects in images, a plurality of object proposals and one or more subpart proposals in a same image;
• perform a first filtering of the object proposals;
• for each subpart proposal, match the subpart proposal with a corresponding one of the object proposals remaining after the first filtering, and
• perform a second filtering of the one object proposals remaining after the first filtering and not matched with any of the one or more subpart proposals,
• wherein the first filtering and the second filtering are based on classification confidence scores and proximity scores of the object proposals, and wherein the second filtering is statistically more aggressive than the first filtering.