  Video Generation is a relatively new and yet popular subject in machine
learning due to its vast variety of potential applications and its numerous
challenges. Current methods in Video Generation provide the user with little or
no control over the exact specification of how the objects in the generate
video are to be moved and located at each frame, that is, the user can't
explicitly control how each object in the video should move. In this paper we
propose a novel method that allows the user to move any number of objects of a
single initial frame just by drawing bounding boxes over those objects and then
moving those boxes in the desired path. Our model utilizes two Autoencoders to
fully decompose the motion and content information in a video and achieves
results comparable to well-known baseline and state of the art methods.
