mlsanityData to 7 Oct 2026

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

arXiv 2208.01618 ↗First posted 2 Aug 2022cs.CV cs.CL cs.GRcited by 2,231

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Cited by 1,161 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Text-to-image models offer unprecedented freedom to guide creation through natural language. Yet, it is unclear how such freedom can be exercised to generate images of specific unique concepts, modify their appearance, or compose them in new roles and novel scenes. In other words, we ask: how can we use language-guided models to turn our cat into a painting, or imagine a new product based on our favorite toy? Here we present a simple approach that allows such creative freedom. Using only 3-5 images of a user-provided concept, like an object or a style, we learn to represent it through new "words" in the embedding space of a frozen text-to-image model. These "words" can be composed into natural language sentences, guiding personalized creation in an intuitive way. Notably, we find evidence that a single word embedding is sufficient for capturing unique and varied concepts. We compare our approach to a wide range of baselines, and demonstrate that it can more faithfully portray the concepts across a range of applications and tasks. Our code, data and new words will be available at: https://textual-inversion.github.io

Key facts. Cited by 2,231 papers in the map (data through 7 Oct 2026). Builds on 63 of its 94 references that are in the map. First posted on arXiv 2 Aug 2022.

Builds on

63 of 94 references.

References · 63

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  6. 2020Denoising Diffusion Implicit Modelscited by 9,655
  7. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  8. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  9. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  10. 2022Classifier-Free Diffusion Guidancecited by 5,717
  11. 2017Neural Discrete Representation Learningcited by 4,650
  12. 2021Zero-Shot Text-to-Image Generationcited by 4,276
38 more
  1. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  2. 2021Learning to Prompt for Vision-Language Modelscited by 2,269
  3. 2021LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairscited by 1,544
  4. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,287
  5. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  6. 2019StarGAN v2: Diverse Image Synthesis for Multiple Domainscited by 1,095
  7. 2021CLIP-Adapter: Better Vision-Language Models with Feature Adapterscited by 1,021
  8. 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 990
  9. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
  10. 2020Encoding in Style: a StyleGAN Encoder for Image-to-Image Translationcited by 727
  11. 2022Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distributioncited by 722
  12. 2019Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?cited by 675
  13. 2017AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networkscited by 664
  14. 2021Multimodal Few-Shot Learning with Frozen Language Modelscited by 657
  15. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  16. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  17. 2021Designing an Encoder for StyleGAN Image Manipulationcited by 542
  18. 2022TEMOS: Generating diverse human motions from textual descriptionscited by 486
  19. 2022Blended Latent Diffusioncited by 430
  20. 2021Pivotal Tuning for Latent-based Editing of Real Imagescited by 427
  21. 2020In-Domain GAN Inversion for Real Image Editingcited by 420
  22. 2022MotionCLIP: Exposing Human Motion Generation to CLIP Spacecited by 406
  23. 2021GAN Inversion: A Surveycited by 366
  24. 2019Image2StyleGAN++: How to Edit the Embedded Images?cited by 356
  25. 2016Generative Visual Manipulation on the Natural Image Manifoldcited by 348
  26. 2021Text2Mesh: Text-Driven Neural Stylization for Meshescited by 332
  27. 2020Three Approaches for Personalization with Applications to Federated Learningcited by 321
  28. 2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
  29. 2020Personalized Federated Learning: A Meta-Learning Approachcited by 309
  30. 2019DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesiscited by 308
  31. 2022VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidancecited by 285
  32. 2019Improving Federated Learning Personalization via Model Agnostic Meta Learningcited by 264
  33. 2021Cross-Modal Contrastive Learning for Text-to-Image Generationcited by 259
  34. 2021Personalized Federated Learning using Hypernetworkscited by 210
  35. 2021HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editingcited by 208
  36. 2021Few-shot Image Generation via Cross-domain Correspondencecited by 206
  37. 2021CLIPstyler: Image Style Transfer with a Single Text Conditioncited by 203
  38. 2019Image Processing Using Multi-Code GAN Priorcited by 185

50 most cited of 63 All 63 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 56; 2023: 530; 2024: 724; 2025: 634; 2026: 287.

2,231 papers.

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  1. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  2. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  3. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
  4. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  5. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
  6. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,465
  7. 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,439
  8. 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuningcited by 1,418
  9. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  10. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
  11. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,099
  12. 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 960
38 more
  1. 2022Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generationcited by 958
  2. 2023Training Diffusion Models with Reinforcement Learningcited by 939
  3. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
  4. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897
  5. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
  6. 2024Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Surveycited by 641
  7. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 640
  8. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 638
  9. 2023NExT-GPT: Any-to-Any Multimodal LLMcited by 610
  10. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
  11. 2023Erasing Concepts from Diffusion Modelscited by 530
  12. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  13. 2022Paint by Example: Exemplar-based Image Editing with Diffusion Modelscited by 489
  14. 2024Evaluating Text-to-Visual Generation with Image-to-Text Generationcited by 465
  15. 2023Generative Multimodal Models are In-Context Learnerscited by 446
  16. 2023BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editingcited by 438
  17. 2024InstantID: Zero-shot Identity-Preserving Generation in Secondscited by 431
  18. 2023Aligning Text-to-Image Models using Human Feedbackcited by 418
  19. 2023ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generationcited by 414
  20. 2023AnyDoor: Zero-shot Object-level Image Customizationcited by 411
  21. 2023Analyzing and Improving the Training Dynamics of Diffusion Modelscited by 396
  22. 2023Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priorscited by 395
  23. 2024OmniGen: Unified Image Generationcited by 388
  24. 2023Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Modelscited by 358
  25. 2023InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuningcited by 343
  26. 2023SVDiff: Compact Parameter Space for Diffusion Fine-Tuningcited by 338
  27. 2024OminiControl: Minimal and Universal Control for Diffusion Transformercited by 334
  28. 2023Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discoverycited by 329
  29. 2023ControlVideo: Training-free Controllable Text-to-Video Generationcited by 324
  30. 2023PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embeddingcited by 324
  31. 2023Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Modelscited by 323
  32. 2023FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attentioncited by 313
  33. 2023Video-P2P: Video Editing with Cross-attention Controlcited by 312
  34. 2023Ablating Concepts in Text-to-Image Diffusion Modelscited by 312
  35. 2023Training-Free Layout Control with Cross-Attention Guidancecited by 312
  36. 2023RealFusion: 360deg Reconstruction of Any Object from a Single Imagecited by 305
  37. 2023Diffusion Self-Guidance for Controllable Image Generationcited by 305
  38. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 303

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