Abstract: Example implementations include a method, apparatus and computer-readable medium for object classification, including executing a multi-class object classification model (OCM) on an input image depicting an object, wherein the multi-class OCM is configured to output, for each respective class of a plurality of classes, a respective confidence score indicative of a likelihood of the object being of a member the respective class. The implementations further include detecting a plurality of confidence scores outputted by the multi-class OCM that are within a threshold range, wherein classes associated with the plurality of confidence scores are candidate classes of the object. Additionally, the implementations further include executing, on the input image, a single-class OCM for each of the candidate classes and outputting a final class for the object in the input image based on a result of each single-class OCM.

Abstract: Example implementations include a method, apparatus and computer-readable medium for object classification, including executing a multi-class object classification model (OCM) on an input image depicting an object, wherein the multi-class OCM is configured to output, for each respective class of a plurality of classes, a respective confidence score indicative of a likelihood of the object being of a member the respective class. The implementations further include detecting a plurality of confidence scores outputted by the multi-class OCM that are within a threshold range, wherein classes associated with the plurality of confidence scores are candidate classes of the object. Additionally, the implementations further include executing, on the input image, a single-class OCM for each of the candidate classes and outputting a final class for the object in the input image based on a result of each single-class OCM.