mlsanityData to 7 Oct 2026

Universal Style Transfer via Feature Transforms

arXiv 1705.08086 ↗First posted 23 May 2017cs.CVcited by 352

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Cited by 42 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Universal style transfer aims to transfer arbitrary visual styles to content images. Existing feed-forward based methods, while enjoying the inference efficiency, are mainly limited by inability of generalizing to unseen styles or compromised visual quality. In this paper, we present a simple yet effective method that tackles these limitations without training on any pre-defined styles. The key ingredient of our method is a pair of feature transforms, whitening and coloring, that are embedded to an image reconstruction network. The whitening and coloring transforms reflect a direct matching of feature covariance of the content image to a given style image, which shares similar spirits with the optimization of Gram matrix based cost in neural style transfer. We demonstrate the effectiveness of our algorithm by generating high-quality stylized images with comparisons to a number of recent methods. We also analyze our method by visualizing the whitened features and synthesizing textures via simple feature coloring.

Key facts. Cited by 352 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 May 2017.

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Citing papers per year: 2021: 67; 2022: 83; 2023: 83; 2024: 45; 2025: 42; 2026: 32.

352 papers.

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  1. 2022Inversion-Based Style Transfer with Diffusion Modelscited by 290
  2. 2023Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylizationcited by 251
  3. 2021RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whiteningcited by 213
  4. 2021More Control for Free! Image Synthesis with Semantic Diffusion Guidancecited by 211
  5. 2021CLIPstyler: Image Style Transfer with a Single Text Conditioncited by 203
  6. 2023ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAscited by 194
  7. 2021StyTr2: Image Style Transfer with Transformerscited by 186
  8. 2021AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfercited by 178
  9. 2021StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generatorscited by 164
  10. 2023StyleDiffusion: Controllable Disentangled Style Transfer via Diffusion Modelscited by 154
  11. 2022ARF: Artistic Radiance Fieldscited by 147
  12. 2022StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learningcited by 140
38 more
  1. 2022NeRF-Art: Text-Driven Neural Radiance Fields Stylizationcited by 126
  2. 2022Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalizationcited by 122
  3. 2021ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flowscited by 113
  4. 2021Stylizing 3D Scene via Implicit Representation and HyperNetworkcited by 103
  5. 2021Talk-to-Edit: Fine-Grained Facial Editing via Dialogcited by 102
  6. 2022Domain Enhanced Arbitrary Image Style Transfer via Contrastive Learningcited by 93
  7. 2023StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fieldscited by 79
  8. 2022Semantic-Aware Domain Generalized Segmentationcited by 78
  9. 2021Learning to Stylize Novel Viewscited by 76
  10. 2022WildNet: Learning Domain Generalized Semantic Segmentation from the Wildcited by 75
  11. 2021Enhancing Photorealism Enhancementcited by 74
  12. 2022Physical Adversarial Attack meets Computer Vision: A Decade Surveycited by 66
  13. 2022Motion Puzzle: Arbitrary Motion Style Transfer by Body Partcited by 64
  14. 2023A Comprehensive Survey on Segment Anything Model for Vision and Beyondcited by 64
  15. 20213DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variationscited by 58
  16. 2021Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentationcited by 56
  17. 2021Anycost GANs for Interactive Image Synthesis and Editingcited by 54
  18. 2023Cross-Ray Neural Radiance Fields for Novel-view Synthesis from Unconstrained Image Collectionscited by 54
  19. 2021Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigationcited by 53
  20. 2021JoJoGAN: One Shot Face Stylizationcited by 49
  21. 2022ArtFID: Quantitative Evaluation of Neural Style Transfercited by 49
  22. 2021BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generationcited by 47
  23. 2021Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expertscited by 46
  24. 2022Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspectivecited by 46
  25. 2022CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfercited by 46
  26. 20213D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Imagecited by 45
  27. 2021Rethinking Style Transfer: From Pixels to Parameterized Brushstrokescited by 42
  28. 2023Instance-Aware Domain Generalization for Face Anti-Spoofingcited by 42
  29. 2021Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfercited by 41
  30. 2021Domain-Aware Universal Style Transfercited by 40
  31. 2022Federated Domain Generalization for Image Recognition via Cross-Client Style Transfercited by 40
  32. 2021Image-Based CLIP-Guided Essence Transfercited by 39
  33. 2021DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfercited by 38
  34. 2023Exploiting Diffusion Prior for Generalizable Dense Predictioncited by 37
  35. 2021Language-Driven Image Style Transfercited by 36
  36. 2023Neural Preset for Color Style Transfercited by 36
  37. 2023ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bankcited by 36
  38. 2022Ref-NPR: Reference-Based Non-Photorealistic Radiance Fields for Controllable Scene Stylizationcited by 35

50 most cited of 352 All 352 (JSON)