DeepFlash: Turning a Flash Selfie into a Studio Portrait
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Abstract (arXiv)
We present a method for turning a flash selfie taken with a smartphone into a photograph as if it was taken in a studio setting with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in an ad-hoc acquisition campaign. Each pair consists of one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend defects introduced by a close-up camera flash, such as specular highlights, shadows, skin shine, and flattened images.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jan 2019.
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Citing papers per year: 2022: 2; 2023: 2.
4 papers.
- 2023Total Selfie: Generating Full-Body Selfiescited by 5
- 2022Deep Portrait Delightingcited by 4
- 2023Computational Flash Photography through Intrinsicscited by 4
- 2022TreeSketchNet: From Sketch To 3D Tree Parameters Generationcited by 2
- 2023Total Selfie: Generating Full-Body Selfies28 Aug 2023
- 2023Computational Flash Photography through Intrinsics9 Jun 2023
- 2022TreeSketchNet: From Sketch To 3D Tree Parameters Generation25 Jul 2022
- 2022Deep Portrait Delighting22 Mar 2022