mlsanityData to 7 Oct 2026

A Learned Representation For Artistic Style

arXiv 1610.07629 ↗First posted 24 Oct 2016cs.CV cs.LGcited by 340

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Abstract (arXiv)

The diversity of painting styles represents a rich visual vocabulary for the construction of an image. The degree to which one may learn and parsimoniously capture this visual vocabulary measures our understanding of the higher level features of paintings, if not images in general. In this work we investigate the construction of a single, scalable deep network that can parsimoniously capture the artistic style of a diversity of paintings. We demonstrate that such a network generalizes across a diversity of artistic styles by reducing a painting to a point in an embedding space. Importantly, this model permits a user to explore new painting styles by arbitrarily combining the styles learned from individual paintings. We hope that this work provides a useful step towards building rich models of paintings and offers a window on to the structure of the learned representation of artistic style.

Key facts. Cited by 340 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Oct 2016.

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Citing papers per year: 2021: 100; 2022: 86; 2023: 66; 2024: 41; 2025: 29; 2026: 18.

340 papers.

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  1. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  2. 2021Generalizing to Unseen Domains: A Survey on Domain Generalizationcited by 762
  3. 2021Domain Generalization: A Surveycited by 760
  4. 2021Domain Generalization with MixStylecited by 563
  5. 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 313
  6. 2023Photorealistic Video Generation with Diffusion Modelscited by 304
  7. 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
  8. 2021Robust Motion In-betweeningcited by 223
  9. 2021Large Scale Image Completion via Co-Modulated Generative Adversarial Networkscited by 219
  10. 2021StyTr2: Image Style Transfer with Transformerscited by 186
  11. 2021AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfercited by 178
  12. 2021DriveGAN: Towards a Controllable High-Quality Neural Simulationcited by 125
38 more
  1. 2022MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generationcited by 125
  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. 2021NeRF-VAE: A Geometry Aware 3D Scene Generative Modelcited by 111
  5. 2021LEAP: Learning Articulated Occupancy of Peoplecited by 107
  6. 2024Measuring Style Similarity in Diffusion Modelscited by 106
  7. 2022A Comprehensive Survey of Image Augmentation Techniques for Deep Learningcited by 95
  8. 2022Domain Enhanced Arbitrary Image Style Transfer via Contrastive Learningcited by 93
  9. 2021Colorization Transformercited by 89
  10. 2021Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentationcited by 88
  11. 2022Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentationcited by 88
  12. 2023Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Trainingcited by 85
  13. 2022EnvEdit: Environment Editing for Vision-and-Language Navigationcited by 83
  14. 2022VIDM: Video Implicit Diffusion Modelscited by 78
  15. 2024CSGO: Content-Style Composition in Text-to-Image Generationcited by 76
  16. 2023Free3D: Consistent Novel View Synthesis without 3D Representationcited by 72
  17. 2021Region-aware Adaptive Instance Normalization for Image Harmonizationcited by 71
  18. 2022Real-Time Style Modelling of Human Locomotion via Feature-Wise Transformations and Local Motion Phasescited by 71
  19. 2021Aligning Latent and Image Spaces to Connect the Unconnectablecited by 70
  20. 2022Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentationcited by 69
  21. 2021MixStyle Neural Networks for Domain Generalization and Adaptationcited by 64
  22. 2021High Fidelity Visualization of What Your Self-Supervised Representation Knows Aboutcited by 64
  23. 2023Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Studycited by 64
  24. 2024StyleShot: A Snapshot on Any Stylecited by 60
  25. 2021Conditional Deformable Image Registration with Convolutional Neural Networkcited by 59
  26. 2021Rebooting ACGAN: Auxiliary Classifier GANs with Stable Trainingcited by 57
  27. 2023A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyondcited by 55
  28. 2021Text to Image Generation with Semantic-Spatial Aware GANcited by 53
  29. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  30. 2022Occluded Human Mesh Recoverycited by 52
  31. 2023CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalizationcited by 51
  32. 2021Diverse Semantic Image Synthesis via Probability Distribution Modelingcited by 49
  33. 2022ArtFID: Quantitative Evaluation of Neural Style Transfercited by 49
  34. 2021Style Normalization and Restitution for Domain Generalization and Adaptationcited by 46
  35. 2022CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfercited by 46
  36. 20213D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Imagecited by 45
  37. 2021Source-Free Open Compound Domain Adaptation in Semantic Segmentationcited by 43
  38. 2021Rethinking Style Transfer: From Pixels to Parameterized Brushstrokescited by 42

50 most cited of 340 All 340 (JSON)