Few-shot object detection method

Abstract

A few-shot object detection method includes: sending a weight of a backbone network and a weight of a feature pyramid to a detection network; generating candidate regions, in which the candidate regions derived from a result of foreground-and-background classification and regression of output features of the visual representation backbone network by a region proposal network; generating candidate region features of a uniform size using a pooling operator based on the candidate regions, and performing location regression, content classification and fine-grained feature mining on the candidate region features of the uniform size; establishing fine-grained positive sample pairs and negative sample pairs through the fine-grained feature mining, and performing comparative learning between fine-grained features of the candidate regions; and generating a loss function according to a strategy in fine-grained feature mining, and updating detection network parameters by calculating based on the loss function.