A review of image and video colorization: From analogies to deep learning  

作　　者：Shu-Yu Chen Jia-Qi Zhang You-You Zhao Paul L.Rosin Yu-Kun Lai Lin Gao 

机构地区：[1]Beijing Key Laboratory of Mobile Computing and Pervasive Device,Institute of Computing Technology,Chinese Academy of Sciences,Beijing,China [2]Beihang University,Beijing,China [3]University of California,Santa Cruz,CA,US [4]Cardiff University,Wales,UK [5]University of Chinese Academy of Sciences,Beijing,China

出　　处：《Visual Informatics》2022年第3期51-68,共18页可视信息学（英文）

基　　金：This work was supported by grants from the National Nat-ural Science Foundation of China(No.61872440,No.62061136007 and No.62102403);the Beijing Municipal Natural Science Foun-dation for Distinguished Young Scholars(No.JQ21013);the Youth Innovation Promotion Association CAS,Royal Society Newton Advanced Fellowship(No.NAF\R2\192151);the Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University(No.VRLAB2022C07).

摘　　要：Image colorization is a classic and important topic in computer graphics,where the aim is to add color to a monochromatic input image to produce a colorful result.In this survey,we present the history of colorization research in chronological order and summarize popular algorithms in this field.Early work on colorization mostly focused on developing techniques to improve the colorization quality.In the last few years,researchers have considered more possibilities such as combining colorization with NLP(natural language processing)and focused more on industrial applications.To better control the color,various types of color control are designed,such as providing reference images or color-scribbles.We have created a taxonomy of the colorization methods according to the input type,divided into grayscale,sketch-based and hybrid.The pros and cons are discussed for each algorithm,and they are compared according to their main characteristics.Finally,we discuss how deep learning,and in particular Generative Adversarial Networks(GANs),has changed this field.

关 键 词：Image colorization Sketch colorization Manga colorization 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]