mlsanityData to 14 Oct 2026

A Neural Algorithm of Artistic Style

arXiv 1508.06576 ↗First posted 26 Aug 2015cs.CV cs.NE q-bio.NCcited by 483

Not on the map. Why?

Cited by 50 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However, in other key areas of visual perception such as object and face recognition near-human performance was recently demonstrated by a class of biologically inspired vision models called Deep Neural Networks. Here we introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality. The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the striking similarities between performance-optimised artificial neural networks and biological vision, our work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery.

Key facts. Cited by 483 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Aug 2015.

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Citing papers per year: 2021: 105; 2022: 84; 2023: 101; 2024: 92; 2025: 69; 2026: 32.

483 papers.

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  1. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,611
  2. 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Datacited by 337
  3. 2025VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulnesscited by 315
  4. 2023Multisample Flow Matching: Straightening Flows with Minibatch Couplingscited by 278
  5. 2023Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylizationcited by 254
  6. 2021Neural Head Avatars from Monocular RGB Videoscited by 213
  7. 2023StyleDrop: Text-to-Image Generation in Any Stylecited by 199
  8. 2021CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoderscited by 187
  9. 2025WorldScore: A Unified Evaluation Benchmark for World Generationcited by 156
  10. 2024AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Taskscited by 154
  11. 2022StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learningcited by 140
  12. 2023Cross-Image Attention for Zero-Shot Appearance Transfercited by 136
38 more
  1. 2021UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Modelscited by 133
  2. 2022Learning What Not to Segment: A New Perspective on Few-Shot Segmentationcited by 120
  3. 2021ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flowscited by 113
  4. 2021Counterfactual Generative Networkscited by 111
  5. 2024Measuring Style Similarity in Diffusion Modelscited by 109
  6. 2023A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?cited by 84
  7. 2021Generalization and Robustness Implications in Object-Centric Learningcited by 81
  8. 2021Input Similarity from the Neural Network Perspectivecited by 79
  9. 2022Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfercited by 78
  10. 2022Real-Time Style Modelling of Human Locomotion via Feature-Wise Transformations and Local Motion Phasescited by 72
  11. 2022Unified Implicit Neural Stylizationcited by 67
  12. 2023A Comprehensive Review of Data-Driven Co-Speech Gesture Generationcited by 66
  13. 2021Making Images Real Again: A Comprehensive Survey on Deep Image Compositioncited by 63
  14. 2022MagicMix: Semantic Mixing with Diffusion Modelscited by 63
  15. 2026Scaling Text-to-Image Diffusion Transformers with Representation Autoencoderscited by 53
  16. 2023Conditional Generation of Audio from Video via Foley Analogiescited by 52
  17. 2024UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Modelscited by 50
  18. 2021Stochastic Image-to-Video Synthesis using cINNscited by 49
  19. 2022UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scenecited by 47
  20. 2023LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Imagescited by 46
  21. 20213D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Imagecited by 45
  22. 2024Image Sculpting: Precise Object Editing with 3D Geometry Controlcited by 45
  23. 2021Zero-shot Adversarial Quantizationcited by 44
  24. 2024Diffusion Model-Based Video Editing: A Surveycited by 44
  25. 2021SinGAN-Seg: Synthetic training data generation for medical image segmentationcited by 43
  26. 2022Modeling Image Composition for Complex Scene Generationcited by 43
  27. 2023Loss Functions and Metrics in Deep Learningcited by 42
  28. 2021Context-Aware Layout to Image Generation with Enhanced Object Appearancecited by 41
  29. 2023Pre-trained Trojan Attacks for Visual Recognitioncited by 39
  30. 2023Idea2Img: Iterative Self-Refinement with GPT-4V(ision) for Automatic Image Design and Generationcited by 38
  31. 2021Language-Driven Image Style Transfercited by 37
  32. 2023Training-free Content Injection using h-space in Diffusion Modelscited by 36
  33. 2024An image speaks a thousand words, but can everyone listen? On image transcreation for cultural relevancecited by 36
  34. 2024Customizing Text-to-Image Models with a Single Image Paircited by 36
  35. 2021Progressive Temporal Feature Alignment Network for Video Inpaintingcited by 35
  36. 2021Image Inpainting by End-to-End Cascaded Refinement with Mask Awarenesscited by 35
  37. 2021Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safetycited by 35
  38. 2021Sound-Guided Semantic Image Manipulationcited by 35

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