IIIT Hyderabad Publications |
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Defocus Magnification using Conditional Adversarial NetworksAuthors: Parikshit Sakurikar,Ishit Mehta,P J Narayanan Conference: IEEE Winter Conf. on Applications of Computer Vision, 2019 (WACV-2019 2019) Location Hawaii, USA Date: 2019-01-08 Report no: IIIT/TR/2019/5 AbstractDefocus magnification is the process of rendering a shallow depth-of-field in an image captured using a camera with a narrow aperture. Defocus magnification is a useful tool in photography for emphasis on the subject and for highlighting background bokeh. Estimating the per-pixel blur kernel or the depth-map of the scene followed by spatially-varying re-blurring is the standard approach to defocus magnification. We propose a single-step approach that directly converts a narrow-aperture image to a wide-aperture image. We use a conditional adversarial network trained on multi-aperture images created from light-fields. We use a novel loss term based on a composite focus measure to improve generalization and show high quality defocus magnification. Full paper: pdf Centre for Education Technology and Learning Science |
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