Digital images are versatile nowadays. However, captured images may not contain the exact content of interest. For example, an image may contain extra objects/persons that are not intended to be included. It is therefore highly demanding to develop more intelligence image manipulation techniques. Recent advances in deep learning and generative adversarial networks provide a much more powerful tool for interactive image manipulation, by adjusting the network layers. The project involves implementation and experiments with deep neural networks for different effects of image manipulation.