mlsanityData to 7 Oct 2026

An Overview of Color Transfer and Style Transfer for Images and Videos

arXiv 2204.13339 ↗First posted 28 Apr 2022cs.CV cs.GRcited by 5

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Abstract (arXiv)

Image or video appearance features (e.g., color, texture, tone, illumination, and so on) reflect one's visual perception and direct impression of an image or video. Given a source image (video) and a target image (video), the image (video) color transfer technique aims to process the color of the source image or video (note that the source image or video is also referred to the reference image or video in some literature) to make it look like that of the target image or video, i.e., transferring the appearance of the target image or video to that of the source image or video, which can thereby change one's perception of the source image or video. As an extension of color transfer, style transfer refers to rendering the content of a target image or video in the style of an artist with either a style sample or a set of images through a style transfer model. As an emerging field, the study of style transfer has attracted the attention of a large number of researchers. After decades of development, it has become a highly interdisciplinary research with a variety of artistic expression styles can be achieved. This paper provides an overview of color transfer and style transfer methods over the past years.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 30 of its 125 references that are in the map. First posted on arXiv 28 Apr 2022.

Builds on

30 of 125 references.

References · 30

  1. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  2. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
  3. 2017Universal Style Transfer via Feature Transformscited by 352
  4. 2017Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesiscited by 215
  5. 2018Arbitrary Style Transfer with Style-Attentional Networkscited by 197
  6. 2016Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networkscited by 192
  7. 2021StyTr2: Image Style Transfer with Transformerscited by 186
  8. 2016Single-Image Depth Perception in the Wildcited by 179
  9. 2016Texture Networks: Feed-forward Synthesis of Textures and Stylized Imagescited by 173
  10. 2017Visual Attribute Transfer through Deep Image Analogycited by 123
  11. 2016Controlling Perceptual Factors in Neural Style Transfercited by 99
  12. 2017Coherent Online Video Style Transfercited by 96
18 more
  1. 2017StyleBank: An Explicit Representation for Neural Image Style Transfercited by 89
  2. 2020Arbitrary Video Style Transfer via Multi-Channel Correlationcited by 84
  3. 2020Arbitrary Style Transfer via Multi-Adaptation Networkcited by 70
  4. 2017Multi-style Generative Network for Real-time Transfercited by 61
  5. 2017Diversified Texture Synthesis with Feed-forward Networkscited by 59
  6. 2018A Style-Aware Content Loss for Real-time HD Style Transfercited by 58
  7. 2019Attention-aware Multi-stroke Style Transfercited by 47
  8. 2017Artistic style transfer for videos and spherical imagescited by 45
  9. 2018Stroke Controllable Fast Style Transfer with Adaptive Receptive Fieldscited by 33
  10. 2016Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfercited by 30
  11. 2018ReCoNet: Real-time Coherent Video Style Transfer Networkcited by 26
  12. 2020A Content Transformation Block For Image Style Transfercited by 19
  13. 2013Image color transfer to evoke different emotions based on color combinationscited by 7
  14. 2017Progressive Color Transfer with Dense Semantic Correspondencescited by 5
  15. 2021Binaural Audio Generation via Multi-task Learningcited by 5
  16. 2018Learning from Multi-domain Artistic Images for Arbitrary Style Transfercited by 4
  17. 2016DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Moviescited by 2
  18. 2019Depth-Aware Arbitrary Style Transfer Using Instance Normalizationcited by 1

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 1.

5 papers.

  1. 2023Dequantization and Color Transfer with Diffusion Modelscited by 4
  2. 2024Efficient approximation of Earth Mover's Distance Based on Nearest Neighbor Searchcited by 3
  3. 2022PTGCF: Printing Texture Guided Color Fusion for Impressionism Oil Painting Style Renderingcited by 1
  4. 2024A Multiscale Gradient Fusion Method for Edge Detection in Color Images Utilizing the CBM3D Filtercited by 0
  5. 2025Neural Artistic Style and Color Transfer Using Deep Learningcited by 0