mlsanityData to 14 Oct 2026

Neural Neighbor Style Transfer

arXiv 2203.13215 ↗First posted 24 Mar 2022cs.CV cs.GRcited by 23

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Abstract (arXiv)

We propose Neural Neighbor Style Transfer (NNST), a pipeline that offers state-of-the-art quality, generalization, and competitive efficiency for artistic style transfer. Our approach is based on explicitly replacing neural features extracted from the content input (to be stylized) with those from a style exemplar, then synthesizing the final output based on these rearranged features. While the spirit of our approach is similar to prior work, we show that our design decisions dramatically improve the final visual quality.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). Builds on 31 of its 52 references that are in the map. First posted on arXiv 24 Mar 2022.

Builds on

31 of 52 references.

References · 31

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  4. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  5. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,694
  6. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 2,010
  7. 2017Universal Style Transfer via Feature Transformscited by 354
  8. 2020Swapping Autoencoder for Deep Image Manipulationcited by 215
  9. 2018Arbitrary Style Transfer with Style-Attentional Networkscited by 198
  10. 2017Deep Photo Style Transfercited by 168
  11. 2019Style Transfer by Relaxed Optimal Transport and Self-Similaritycited by 168
  12. 2017Demystifying Neural Style Transfercited by 152
19 more
  1. 2018The Contextual Loss for Image Transformation with Non-Aligned Datacited by 135
  2. 2014Hypercolumns for Object Segmentation and Fine-grained Localizationcited by 128
  3. 2017Visual Attribute Transfer through Deep Image Analogycited by 123
  4. 2018Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decorationcited by 115
  5. 2021ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flowscited by 113
  6. 2016Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesiscited by 102
  7. 2016Controlling Perceptual Factors in Neural Style Transfercited by 100
  8. 2016Fast Patch-based Style Transfer of Arbitrary Stylecited by 92
  9. 2018Arbitrary Style Transfer with Deep Feature Reshufflecited by 75
  10. 2017Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Lossescited by 69
  11. 2018A Style-Aware Content Loss for Real-time HD Style Transfercited by 58
  12. 2019Attention-aware Multi-stroke Style Transfercited by 47
  13. 2020Interactive Video Stylization Using Few-Shot Patch-Based Trainingcited by 43
  14. 2019Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfercited by 36
  15. 2019Multimodal Style Transfer via Graph Cutscited by 32
  16. 2014Feedforward semantic segmentation with zoom-out featurescited by 21
  17. 2019Im2Pencil: Controllable Pencil Illustration from Photographscited by 18
  18. 2016Incorporating long-range consistency in CNN-based texture generationcited by 8
  19. 2018Unpaired High-Resolution and Scalable Style Transfer Using Generative Adversarial Networkscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 4; 2023: 7; 2024: 10; 2025: 1; 2026: 1.

23 papers.

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  1. 2022ARF: Artistic Radiance Fieldscited by 147
  2. 2023Real-World Image Variation by Aligning Diffusion Inversion Chaincited by 37
  3. 2022Ref-NPR: Reference-Based Non-Photorealistic Radiance Fields for Controllable Scene Stylizationcited by 35
  4. 2024StylizedGS: Controllable Stylization for 3D Gaussian Splattingcited by 23
  5. 2024Geometry Transfer for Stylizing Radiance Fieldscited by 16
  6. 2024CoARF: Controllable 3D Artistic Style Transfer for Radiance Fieldscited by 14
  7. 2024StyleTex: Style Image-Guided Texture Generation for 3D Modelscited by 14
  8. 2024Reference-based Controllable Scene Stylization with Gaussian Splattingcited by 12
  9. 2024CTRL-D: Controllable Dynamic 3D Scene Editing with Personalized 2D Diffusioncited by 11
  10. 2024StyleRF-VolVis: Style Transfer of Neural Radiance Fields for Expressive Volume Visualizationcited by 9
  11. 2023Advances in 3D Neural Stylization: A Surveycited by 8
  12. 2022HyperNST: Hyper-Networks for Neural Style Transfercited by 7
11 more
  1. 2023DIFF-NST: Diffusion Interleaving For deFormable Neural Style Transfercited by 5
  2. 2023NeAT: Neural Artistic Tracing for Beautiful Style Transfercited by 4
  3. 2022MultiStyleGAN: Multiple One-shot Image Stylizations using a Single GANcited by 3
  4. 2023Tackling Data Bias in Painting Classification with Style Transfercited by 3
  5. 2023MuVieCAST: Multi-View Consistent Artistic Style Transfercited by 3
  6. 2024S-DyRF: Reference-Based Stylized Radiance Fields for Dynamic Scenescited by 3
  7. 2024WaSt-3D: Wasserstein-2 Distance for Scene-to-Scene Stylization on 3D Gaussianscited by 3
  8. 2025Stylized Structural Patterns for Improved Neural Network Pre-trainingcited by 1
  9. 2023One-Shot Stylization for Full-Body Human Imagescited by 0
  10. 2024ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classificationcited by 0
  11. 2026UniFixer: A Universal Reference-Guided Fixer for Diffusion-Based View Synthesiscited by 0