SYSTEMS AND METHODS FOR PROVIDING CONVOLUTIONAL NEURAL NETWORK BASED IMAGE SYNTHESIS USING STABLE AND CONTROLLABLE PARAMETRIC MODELS, A MULTISCALE SYNTHESIS FRAMEWORK AND NOVEL NETWORK ARCHITECTURES

摘要

Systems and methods for providing convolutional neural network based image synthesis using localized loss functions is disclosed. A fist image including desired content and a second image including a desired style are received. The images are analyzed to determine a local loss function. The first and second images are merged using the local loss function to generate an image that includes the desired content presented in the desired style. Similar processes can also be utilized to generate image hybrids and to perform on-model texture synthesis. In a number of embodiments, Condensed Feature Extraction Networks are also generated using a convolutional neural network previously trained to perform image classification, where the Condensed Feature Extraction Networks approximates intermediate neural activations of the convolutional neural network utilized during training.