Beeble Researchers Attempt to Manipulate Lighting on Digital Image Using AI

Written by autoencoder | Published 2024/12/21
Tech Story Tags: self-supervised-learning | relighting | human-portrait-relighting | physics-guided-architecture | cook-torrance-model | light-surface-interactions | switchlight-framework | self-supervised-pre-training

TLDRResearchers at Beeble AI have developed a method for improving how light and shadows can be applied to human portraits in digital images.via the TL;DR App

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.

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

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


Written by autoencoder | Research & publications on Auto Encoders, revolutionizing data compression and feature learning techniques.
Published by HackerNoon on 2024/12/21