Modeling the lighting in scenes as style for auto white-balance correction

Name: Modeling the lighting in scenes as style for auto white-balance correction
Author: Kınlı, Osman Furkan, Yılmaz, Doğa, Özcan, Barış, Kıraç, Mustafa Furkan

İsim	Modeling the lighting in scenes as style for auto white-balance correction
Yazar	Kınlı, Osman Furkan, Yılmaz, Doğa, Özcan, Barış, Kıraç, Mustafa Furkan
Basım Tarihi:	2023
Basım Yeri	- IEEE
Konu	Algorithms: Computational photography, Image and video synthesis
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-6654-9346-8
Kayıt Numarası	5bbfb02d-cb1c-4940-bcb2-04b63af05ac2
Lokasyon	Computer Science
Tarih	2023
Örnek Metin	Style may refer to different concepts (e.g. painting style, hairstyle, texture, color, filter, etc.) depending on how the feature space is formed. In this work, we propose a novel idea of interpreting the lighting in the single- and multi-illuminant scenes as the concept of style. To verify this idea, we introduce an enhanced auto white-balance (AWB) method that models the lighting in single- and mixed-illuminant scenes as the style factor. Our AWB method does not require any illumination estimation step, yet contains a network learning to generate the weighting maps of the images with different WB settings. Proposed network utilizes the style information, extracted from the scene by a multi-head style extraction module. AWB correction is completed after blending these weighting maps and the scene. Experiments on single- and mixed-illuminant datasets demonstrate that our proposed method achieves promising correction results when compared to the recent works. This shows that the lighting in the scenes with multiple illuminations can be modeled by the concept of style. Source code and trained models are available on https://github.com/birdortyedi/lighting-as-style-awb-correction.
DOI	10.1109/WACV56688.2023.00488

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Modeling the lighting in scenes as style for auto white-balance correction

Yazar Kınlı, Osman Furkan, Yılmaz, Doğa, Özcan, Barış, Kıraç, Mustafa Furkan

Basım Tarihi 2023

Basım Yeri - IEEE

Konu Algorithms: Computational photography, Image and video synthesis

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-6654-9346-8

Kayıt Numarası 5bbfb02d-cb1c-4940-bcb2-04b63af05ac2

Lokasyon Computer Science

Tarih 2023

Örnek Metin Style may refer to different concepts (e.g. painting style, hairstyle, texture, color, filter, etc.) depending on how the feature space is formed. In this work, we propose a novel idea of interpreting the lighting in the single- and multi-illuminant scenes as the concept of style. To verify this idea, we introduce an enhanced auto white-balance (AWB) method that models the lighting in single- and mixed-illuminant scenes as the style factor. Our AWB method does not require any illumination estimation step, yet contains a network learning to generate the weighting maps of the images with different WB settings. Proposed network utilizes the style information, extracted from the scene by a multi-head style extraction module. AWB correction is completed after blending these weighting maps and the scene. Experiments on single- and mixed-illuminant datasets demonstrate that our proposed method achieves promising correction results when compared to the recent works. This shows that the lighting in the scenes with multiple illuminations can be modeled by the concept of style. Source code and trained models are available on https://github.com/birdortyedi/lighting-as-style-awb-correction.

DOI 10.1109/WACV56688.2023.00488