1. An object recognition method based on weakly supervised learning, the method comprising: training a convolutional neural network (CNN)-based object recognition model using a training target image by using an object recognition apparatus; and recognizing an object of interest included in a recognition target image using the trained object recognition model by using the object recognition apparatus, wherein the object recognition model comprises a convolution layer which extracts a plurality of feature maps from the training target image and a deconvolution layer which increases sizes of the feature maps, and a weight matrix of a filter used in the deconvolution layer is obtained by transposing a weight matrix of a filter used in the convolution layer corresponding to the deconvolution layer.