SEMANTIC IMAGE SEGMENTATION METHOD BASED ON DEEP-LEARNING AND APPARATUS THEREOF

摘要

A deep learning-based image segmentation method and apparatus thereof according to an embodiment of the present invention relates to a method and apparatus for segmenting a face in a cartoon image using a deep learning neural network. The deep learning-based image segmentation apparatus according to an embodiment of the present invention receives a training data set including a target domain image as a cartoon image, a source domain image as a real-life image, and a correct answer label in which a face in the source domain image is segmented. A communication unit; A storage unit for storing a deep learning model; And a processor that trains the deep learning model to transform a face into an image region using the training data set, and performs face regionization of the target domain image using the trained deep learning model. The processor extracts a common content space from the source domain image using the deep learning model and extracts a common content space from the target domain image, and the common content space extracted from the source domain image is a face region of the source domain image. And the common content space extracted from the target domain image is a feature expression representing the face area of the target domain image, and the processor uses the deep learning model to extract the common content space from the source domain image. The training may be performed to make the image region, and the face region of the target domain image may be performed using a common content space extracted from the target domain image. The deep learning-based image segmentation method and apparatus thereof according to an embodiment of the present invention may transform a cartoon image by training a neural network without a training data set for the cartoon image.