  We introduce Text2Cinemagraph, a fully automated method for creating
cinemagraphs from text descriptions - an especially challenging task when
prompts feature imaginary elements and artistic styles, given the complexity of
interpreting the semantics and motions of these images. We focus on
cinemagraphs of fluid elements, such as flowing rivers, and drifting clouds,
which exhibit continuous motion and repetitive textures. Existing single-image
animation methods fall short on artistic inputs, and recent text-based video
methods frequently introduce temporal inconsistencies, struggling to keep
certain regions static. To address these challenges, we propose an idea of
synthesizing image twins from a single text prompt - a pair of an artistic
image and its pixel-aligned corresponding natural-looking twin. While the
artistic image depicts the style and appearance detailed in our text prompt,
the realistic counterpart greatly simplifies layout and motion analysis.
Leveraging existing natural image and video datasets, we can accurately segment
the realistic image and predict plausible motion given the semantic
information. The predicted motion can then be transferred to the artistic image
to create the final cinemagraph. Our method outperforms existing approaches in
creating cinemagraphs for natural landscapes as well as artistic and
other-worldly scenes, as validated by automated metrics and user studies.
Finally, we demonstrate two extensions: animating existing paintings and
controlling motion directions using text.
