  Smartphone cameras today are increasingly approaching the versatility and
quality of professional cameras through a combination of hardware and software
advancements. However, fixed aperture remains a key limitation, preventing
users from controlling the depth of field (DoF) of captured images. At the same
time, many smartphones now have multiple cameras with different fixed apertures
-- specifically, an ultra-wide camera with wider field of view and deeper DoF
and a higher resolution primary camera with shallower DoF. In this work, we
propose $\text{DC}^2$, a system for defocus control for synthetically varying
camera aperture, focus distance and arbitrary defocus effects by fusing
information from such a dual-camera system. Our key insight is to leverage
real-world smartphone camera dataset by using image refocus as a proxy task for
learning to control defocus. Quantitative and qualitative evaluations on
real-world data demonstrate our system's efficacy where we outperform
state-of-the-art on defocus deblurring, bokeh rendering, and image refocus.
Finally, we demonstrate creative post-capture defocus control enabled by our
method, including tilt-shift and content-based defocus effects.
