Abstract. Post-capture control of the focus position of an image is a
useful photographic tool. Changing the focus of a single image involves
the complex task of simultaneously estimating the radiance and the defocus radius of all scene points. We introduce RefocusGAN, a deblurthen-reblur approach to single image refocusing. We train conditional
adversarial networks for deblurring and refocusing using wide-aperture
images created from light-fields. By appropriately conditioning our networks with a focus measure, an in-focus image and a refocus control
parameter ?, we are able to achieve generic free-form refocusing over a
single image