Neural Preset for Color Style Transfer

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

6 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition
PublisherIEEE
Pages14173-14182
ISBN (electronic)9798350301298
ISBN (print)979-8-3503-0130-4
Publication statusPublished - 2023

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919
ISSN (electronic)2575-7075

Conference

Title2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023)
LocationVancouver Convention Center
PlaceCanada
CityVancouver
Period18 - 22 June 2023

Abstract

In this paper, we present a Neural Preset technique to address the limitations of existing color style transfer methods, including visual artifacts, vast memory requirement, and slow style switching speed. Our method is based on two core designs. First, we propose Deterministic Neural Color Mapping (DNCM) to consistently operate on each pixel via an image-adaptive color mapping matrix, avoiding artifacts and supporting high-resolution inputs with a small memory footprint. Second, we develop a two-stage pipeline by dividing the task into color normalization and stylization, which allows efficient style switching by extracting color styles as presets and reusing them on normalized input images. Due to the unavailability of pairwise datasets, we describe how to train Neural Preset via a self-supervised strategy. Various advantages of Neural Preset over existing methods are demonstrated through comprehensive evaluations. Besides, we show that our trained model can naturally support multiple applications without fine-tuning, including low-light image enhancement, underwater image correction, image dehazing, and image harmonization. © 2023 IEEE

Research Area(s)

  • Image and video synthesis and generation

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Neural Preset for Color Style Transfer. / Ke, Zhanghan; Liu, Yuhao; Zhu, Lei et al.
Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, 2023. p. 14173-14182 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review