Deep Convolutional Neural Networks Which Output Images —Semantic Segmentation and Image Generation/Transformation—

Abstract

Initially, the effectiveness of CNNs (Convolutional Neural Network) was proved for image categorization tasks for which a CNN accepts an image as an input and outputs a class probability vector as an output in general. Recently the way to use of CNNs becomes diverse, and CNNs which output images have been commonly used for semantic image segmentation, image transformation and image generation. Then, in this article, we explain CNNs for semantic segmentation in case of weakly supervision as well as full supervision, and CNNs for image generation and transformation which are typically decoder-style CNNs and encoder-decoder-style CNNs.