  Whether to attract viewer attention to a particular object, give the
impression of depth or simply reproduce human-like scene perception, shallow
depth of field images are used extensively by professional and amateur
photographers alike. To this end, high quality optical systems are used in DSLR
cameras to focus on a specific depth plane while producing visually pleasing
bokeh. We propose a physically motivated pipeline to mimic this effect from
all-in-focus stereo images, typically retrieved by mobile cameras. It is
capable to change the focal plane a posteriori at 76 FPS on KITTI images to
enable real-time applications. As our portmanteau suggests, SteReFo
interrelates stereo-based depth estimation and refocusing efficiently. In
contrast to other approaches, our pipeline is simultaneously fully
differentiable, physically motivated, and agnostic to scene content. It also
enables computational video focus tracking for moving objects in addition to
refocusing of static images. We evaluate our approach on the publicly available
datasets SceneFlow, KITTI, CityScapes and quantify the quality of architectural
changes.
