  We propose a method to interactively control the animation of fluid elements
in still images to generate cinemagraphs. Specifically, we focus on the
animation of fluid elements like water, smoke, fire, which have the properties
of repeating textures and continuous fluid motion. Taking inspiration from
prior works, we represent the motion of such fluid elements in the image in the
form of a constant 2D optical flow map. To this end, we allow the user to
provide any number of arrow directions and their associated speeds along with a
mask of the regions the user wants to animate. The user-provided input arrow
directions, their corresponding speed values, and the mask are then converted
into a dense flow map representing a constant optical flow map (FD). We observe
that FD, obtained using simple exponential operations can closely approximate
the plausible motion of elements in the image. We further refine computed dense
optical flow map FD using a generative-adversarial network (GAN) to obtain a
more realistic flow map. We devise a novel UNet based architecture to
autoregressively generate future frames using the refined optical flow map by
forward-warping the input image features at different resolutions. We conduct
extensive experiments on a publicly available dataset and show that our method
is superior to the baselines in terms of qualitative and quantitative metrics.
In addition, we show the qualitative animations of the objects in directions
that did not exist in the training set and provide a way to synthesize videos
that otherwise would not exist in the real world.
