mlsanityData to 7 Oct 2026

Generative Visual Manipulation on the Natural Image Manifold

arXiv 1609.03552 ↗First posted 12 Sep 2016cs.CVcited by 348

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Cited by 59 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Realistic image manipulation is challenging because it requires modifying the image appearance in a user-controlled way, while preserving the realism of the result. Unless the user has considerable artistic skill, it is easy to "fall off" the manifold of natural images while editing. In this paper, we propose to learn the natural image manifold directly from data using a generative adversarial neural network. We then define a class of image editing operations, and constrain their output to lie on that learned manifold at all times. The model automatically adjusts the output keeping all edits as realistic as possible. All our manipulations are expressed in terms of constrained optimization and are applied in near-real time. We evaluate our algorithm on the task of realistic photo manipulation of shape and color. The presented method can further be used for changing one image to look like the other, as well as generating novel imagery from scratch based on user's scribbles.

Key facts. Cited by 348 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Sep 2016.

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Citing papers per year: 2021: 100; 2022: 81; 2023: 84; 2024: 42; 2025: 32; 2026: 9.

348 papers.

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  1. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  2. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  3. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  4. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  5. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
  6. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,099
  7. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  8. 2021Designing an Encoder for StyleGAN Image Manipulationcited by 542
  9. 2023Zero-shot Image-to-Image Translationcited by 503
  10. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  11. 2021Pivotal Tuning for Latent-based Editing of Real Imagescited by 427
  12. 2021GAN Inversion: A Surveycited by 366
38 more
  1. 2023DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editingcited by 293
  2. 2021ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinementcited by 248
  3. 2023P+: Extended Textual Conditioning in Text-to-Image Generationcited by 242
  4. 2021Editing Conditional Radiance Fieldscited by 222
  5. 2023Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifoldcited by 218
  6. 2021HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editingcited by 208
  7. 2022Re-Imagen: Retrieval-Augmented Text-to-Image Generatorcited by 208
  8. 2023Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Modelscited by 203
  9. 2021High-Fidelity GAN Inversion for Image Attribute Editingcited by 197
  10. 2022StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGANcited by 169
  11. 2022RenderDiffusion: Image Diffusion for 3D Reconstruction, Inpainting and Generationcited by 162
  12. 2021EditGAN: High-Precision Semantic Image Editingcited by 156
  13. 2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
  14. 2021Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesiscited by 140
  15. 2021Hyperbolic Deep Neural Networks: A Surveycited by 138
  16. 2024ReNoise: Real Image Inversion Through Iterative Noisingcited by 127
  17. 2023Generalizing Dataset Distillation via Deep Generative Priorcited by 125
  18. 2023A Neural Space-Time Representation for Text-to-Image Personalizationcited by 123
  19. 2023Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervisioncited by 112
  20. 2021Paint by Wordcited by 107
  21. 2021Deep Generative Learning via Schr"odinger Bridgecited by 103
  22. 2021Talk-to-Edit: Fine-Grained Facial Editing via Dialogcited by 102
  23. 2021Instance Localization for Self-supervised Detection Pretrainingcited by 99
  24. 2023Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Modelscited by 98
  25. 2021Only a Matter of Style: Age Transformation Using a Style-Based Regression Modelcited by 92
  26. 2021ShaRF: Shape-conditioned Radiance Fields from a Single Viewcited by 92
  27. 2021GAN-Control: Explicitly Controllable GANscited by 91
  28. 2021Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editingcited by 91
  29. 2021HyperInverter: Improving StyleGAN Inversion via Hypernetworkcited by 85
  30. 2023Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Modelscited by 85
  31. 2021Ensembling Off-the-shelf Models for GAN Trainingcited by 84
  32. 2023A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?cited by 84
  33. 2021Constrained Graphic Layout Generation via Latent Optimizationcited by 83
  34. 2023Circumventing Concept Erasure Methods For Text-to-Image Generative Modelscited by 81
  35. 2022DiffFace: Diffusion-based Face Swapping with Facial Guidancecited by 77
  36. 2021FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizationcited by 71
  37. 2021Unsupervised 3D Shape Completion through GAN Inversioncited by 70
  38. 2022Stitch it in Time: GAN-Based Facial Editing of Real Videoscited by 68

50 most cited of 348 All 348 (JSON)