mlsanityData to 7 Oct 2026

ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows

arXiv 2103.16877 ↗First posted 31 Mar 2021cs.CV eess.IVcited by 113

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Cited by 21 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Universal style transfer retains styles from reference images in content images. While existing methods have achieved state-of-the-art style transfer performance, they are not aware of the content leak phenomenon that the image content may corrupt after several rounds of stylization process. In this paper, we propose ArtFlow to prevent content leak during universal style transfer. ArtFlow consists of reversible neural flows and an unbiased feature transfer module. It supports both forward and backward inferences and operates in a projection-transfer-reversion scheme. The forward inference projects input images into deep features, while the backward inference remaps deep features back to input images in a lossless and unbiased way. Extensive experiments demonstrate that ArtFlow achieves comparable performance to state-of-the-art style transfer methods while avoiding content leak.

Key facts. Cited by 113 papers in the map (data through 7 Oct 2026). Builds on 52 of its 63 references that are in the map. First posted on arXiv 31 Mar 2021.

Builds on

52 of 63 references.

References · 52

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38 more
  1. 2015A Neural Algorithm of Artistic Stylecited by 480
  2. 2017Universal Style Transfer via Feature Transformscited by 352
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  4. 2018WaveGlow: A Flow-based Generative Network for Speech Synthesiscited by 308
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  9. 2019Photorealistic Style Transfer via Wavelet Transformscited by 166
  10. 2017Demystifying Neural Style Transfercited by 152
  11. 2018A Closed-form Solution to Photorealistic Image Stylizationcited by 133
  12. 2017Visual Attribute Transfer through Deep Image Analogycited by 123
  13. 2018Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decorationcited by 115
  14. 2016Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesiscited by 102
  15. 2020Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizationscited by 102
  16. 2016Fast Patch-based Style Transfer of Arbitrary Stylecited by 92
  17. 2017StyleBank: An Explicit Representation for Neural Image Style Transfercited by 89
  18. 2019Dynamic Instance Normalization for Arbitrary Style Transfercited by 83
  19. 2018Arbitrary Style Transfer with Deep Feature Reshufflecited by 75
  20. 2017Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Lossescited by 69
  21. 2017Multi-style Generative Network for Real-time Transfercited by 61
  22. 2020Collaborative Distillation for Ultra-Resolution Universal Style Transfercited by 52
  23. 2018Learning Linear Transformations for Fast Arbitrary Style Transfercited by 48
  24. 2019A Closed-form Solution to Universal Style Transfercited by 42
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  31. 2020Rethinking Image Deraining via Rain Streaks and Vaporscited by 24
  32. 2016Preserving Color in Neural Artistic Style Transfercited by 20
  33. 2017Laplacian-Steered Neural Style Transfercited by 17
  34. 2018Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancementcited by 14
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  38. 2020Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruningcited by 9

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 26; 2023: 30; 2024: 24; 2025: 16; 2026: 14.

113 papers.

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  1. 2022Inversion-Based Style Transfer with Diffusion Modelscited by 290
  2. 2023Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfercited by 194
  3. 2021StyTr2: Image Style Transfer with Transformerscited by 186
  4. 2023StyleDiffusion: Controllable Disentangled Style Transfer via Diffusion Modelscited by 154
  5. 2022ARF: Artistic Radiance Fieldscited by 147
  6. 2022Domain Enhanced Arbitrary Image Style Transfer via Contrastive Learningcited by 93
  7. 2024DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representationscited by 68
  8. 2022ArtFID: Quantitative Evaluation of Neural Style Transfercited by 49
  9. 2024UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Modelscited by 47
  10. 2022CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfercited by 46
  11. 2022DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylizationcited by 45
  12. 2022Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translationcited by 39
38 more
  1. 2023ArtAdapter: Text-to-Image Style Transfer using Multi-Level Style Encoder and Explicit Adaptationcited by 39
  2. 2023AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networkscited by 34
  3. 2022StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesiscited by 32
  4. 2023General Image-to-Image Translation with One-Shot Image Guidancecited by 31
  5. 2025OmniStyle: Filtering High Quality Style Transfer Data at Scalecited by 30
  6. 2022Learning Graph Neural Networks for Image Style Transfercited by 29
  7. 2022SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonizationcited by 24
  8. 2023CAP-VSTNet: Content Affinity Preserved Versatile Style Transfercited by 24
  9. 2022Neural Neighbor Style Transfercited by 23
  10. 2024StylizedGS: Controllable Stylization for 3D Gaussian Splattingcited by 23
  11. 2022AesUST: Towards Aesthetic-Enhanced Universal Style Transfercited by 21
  12. 2022MicroAST: Towards Super-Fast Ultra-Resolution Arbitrary Style Transfercited by 19
  13. 2022QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelitycited by 18
  14. 2023Any-to-Any Style Transfer: Making Picasso and Da Vinci Collaboratecited by 17
  15. 2023Z^*: Zero-shot Style Transfer via Attention Rearrangementcited by 17
  16. 2022All-to-key Attention for Arbitrary Style Transfercited by 16
  17. 2022Name Your Style: An Arbitrary Artist-aware Image Style Transfercited by 14
  18. 2022S2WAT: Image Style Transfer via Hierarchical Vision Transformer using Strips Window Attentioncited by 14
  19. 2024StyleTex: Style Image-Guided Texture Generation for 3D Modelscited by 14
  20. 2021Texture Reformer: Towards Fast and Universal Interactive Texture Transfercited by 12
  21. 2023Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style Transferscited by 12
  22. 2025U-StyDiT: Ultra-high Quality Artistic Style Transfer Using Diffusion Transformerscited by 12
  23. 2022Fine-Grained Image Style Transfer with Visual Transformerscited by 11
  24. 2022Region-aware Knowledge Distillation for Efficient Image-to-Image Translationcited by 10
  25. 2023A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive Learningcited by 10
  26. 2023Learning to Evaluate the Artness of AI-generated Imagescited by 10
  27. 2022Industrial Style Transfer with Large-scale Geometric Warping and Content Preservationcited by 9
  28. 2025Video Color Grading via Look-Up Table Generationcited by 9
  29. 2025AttenST: A Training-Free Attention-Driven Style Transfer Framework with Pre-Trained Diffusion Modelscited by 8
  30. 2022HyperNST: Hyper-Networks for Neural Style Transfercited by 7
  31. 2023Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs Towards Robot-assisted Intubationcited by 6
  32. 2024CreativeSynth: Cross-Art-Attention for Artistic Image Synthesis with Multimodal Diffusioncited by 6
  33. 2024DiffArtist: Towards Structure and Appearance Controllable Image Stylizationcited by 6
  34. 2023WaterFlow: Heuristic Normalizing Flow for Underwater Image Enhancement and Beyondcited by 5
  35. 2024StyleMamba : State Space Model for Efficient Text-driven Image Style Transfercited by 5
  36. 2024Puff-Net: Efficient Style Transfer with Pure Content and Style Feature Fusion Networkcited by 5
  37. 2024Mamba-ST: State Space Model for Efficient Style Transfercited by 5
  38. 2024DiffuseST: Unleashing the Capability of the Diffusion Model for Style Transfercited by 5

50 most cited of 113 All 113 (JSON)