FEATURE MAP PROCESSING METHOD AND RELATED DEVICE

This application relates to the field of artificial intelligence technologies, and provides a feature map processing method and a related device. The method is implemented by invoking a neural network model that includes a plurality of input adaptation branches and a post-processing part. An output of each of the plurality of input adaptation branches is an input of the post-processing part, and each of the plurality of input adaptation branches can downsample a feature map at a different ratio. Specifically, a first feature map is input to one of the plurality of input adaptation branches, to obtain a second feature map, where the one input adaptation branch is determined based on a size of the first feature map and a preset size threshold, the preset size threshold is an upper limit size of an input feature map of the post-processing part, and a size of the second feature map is not greater than the preset size threshold; and the second feature map is input to the post-processing part for post-processing, to obtain a processing result of the first feature map. In embodiments of this application, computing power can be reduced.