Learning method and learning device for updating object detector, based on deep learning, of autonomous vehicle to adapt the object detector to driving circumstance, and updating method and updating device using the same

Abstract

A method for updating an object detector of an autonomous vehicle to adapt the object detector to a driving circumstance is provided. The method includes steps of: a learning device (a) (i) inputting a training image, corresponding to a driving circumstance, into a circumstance-specific object detector to apply (i-1) convolution to the training image to generate a circumstance-specific feature map, (i-2) ROI pooling to the circumstance-specific feature map to generate a circumstance-specific pooled feature map, and (i-3) fully-connected operation to the circumstance-specific pooled feature map to generate circumstance-specific object detection information and (ii) inputting the circumstance-specific feature map into a circumstance-specific ranking network to (ii-1) apply deconvolution to the circumstance-specific feature map and generate a circumstance-specific segmentation map and (ii-2) generate a circumstance-specific rank score via a circumstance-specific discriminator; and (b) training the circumstance-specific object detector, the circumstance-specific deconvolutional layer, the circumstance-specific convolutional layer, and the circumstance-specific discriminator.