Modifications are performed to cause a style of an image to match a different style. A first image is accessed, where the first image has the first style. A second image is also accessed, where the second image has a second style. Subsequent to a deep neural network (DNN) learning these styles, a copy of the first image is fed as input to the DNN. The DNN modifies the first image copy by transitioning the first image copy from being of the first style to subsequently being of the second style. As a consequence, a modified style of the transitioned first image copy bilaterally matches the second style.