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Beeble Researchers Attempt to Manipulate Lighting on Digital Image Using AI

Tags: digital video
DATE POSTED:December 21, 2024

:::info Authors:

(1) Hoon Kim, Beeble AI, and contributed equally to this work;

(2) Minje Jang, Beeble AI, and contributed equally to this work;

(3) Wonjun Yoon, Beeble AI, and contributed equally to this work;

(4) Jisoo Lee, Beeble AI, and contributed equally to this work;

(5) Donghyun Na, Beeble AI, and contributed equally to this work;

(6) Sanghyun Woo, New York University, and contributed equally to this work.

:::

:::tip Editor's Note: This is Part 4 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below.

:::

Table of Links

\ Appendix

3.2. Problem Formulation

\ Figure 2. SwitchLight Architecture. The input source image is decomposed into normal map, lighting, diffuse and specular components. Given these intrinsics, images are re-rendered under target lighting. The architecture integrates the Cook-Torrance reflection model; the final output combines physically-based predictions with neural network enhancements for realistic portrait relighting.

\

:::info This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.

:::

\

Tags: digital video