mlsanityData to 7 Oct 2026

StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis

arXiv 2301.09515 ↗First posted 23 Jan 2023cs.LG cs.CVcited by 212

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Cited by 91 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Text-to-image synthesis has recently seen significant progress thanks to large pretrained language models, large-scale training data, and the introduction of scalable model families such as diffusion and autoregressive models. However, the best-performing models require iterative evaluation to generate a single sample. In contrast, generative adversarial networks (GANs) only need a single forward pass. They are thus much faster, but they currently remain far behind the state-of-the-art in large-scale text-to-image synthesis. This paper aims to identify the necessary steps to regain competitiveness. Our proposed model, StyleGAN-T, addresses the specific requirements of large-scale text-to-image synthesis, such as large capacity, stable training on diverse datasets, strong text alignment, and controllable variation vs. text alignment tradeoff. StyleGAN-T significantly improves over previous GANs and outperforms distilled diffusion models - the previous state-of-the-art in fast text-to-image synthesis - in terms of sample quality and speed.

Key facts. Cited by 212 papers in the map (data through 7 Oct 2026). Builds on 62 of its 73 references that are in the map. First posted on arXiv 23 Jan 2023.

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62 of 73 references.

References · 62

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
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  9. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  10. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  11. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  12. 2022Classifier-Free Diffusion Guidancecited by 5,717
38 more
  1. 2022Generative Adversarial Networkscited by 5,603
  2. 2020Training data-efficient image transformers & distillation through attentioncited by 4,560
  3. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  4. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  5. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  6. 2022A ConvNet for the 2020scited by 3,545
  7. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
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  9. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  10. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  11. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
  12. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  13. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,961
  14. 2018Group Normalizationcited by 1,514
  15. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,287
  16. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,250
  17. 2021Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Conceptscited by 1,209
  18. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  19. 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 990
  20. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
  21. 2021Going deeper with Image Transformerscited by 759
  22. 2016Generative Adversarial Text to Image Synthesiscited by 735
  23. 2022On Distillation of Guided Diffusion Modelscited by 721
  24. 2022Pseudo Numerical Methods for Diffusion Models on Manifoldscited by 695
  25. 2019Interpreting the Latent Space of GANs for Semantic Face Editingcited by 691
  26. 2021FLAVA: A Foundational Language And Vision Alignment Modelcited by 646
  27. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 640
  28. 2020GANSpace: Discovering Interpretable GAN Controlscited by 612
  29. 2022StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasetscited by 489
  30. 2022Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priorscited by 487
  31. 2020Differentiable Augmentation for Data-Efficient GAN Trainingcited by 361
  32. 2020StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flowscited by 348
  33. 2021Deep ViT Features as Dense Visual Descriptorscited by 327
  34. 2022VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidancecited by 285
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  38. 2022The Role of ImageNet Classes in Fr'echet Inception Distancecited by 211

50 most cited of 62 All 62 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 69; 2024: 74; 2025: 47; 2026: 22.

212 papers.

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  1. 2024Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Predictioncited by 1,005
  2. 2023One-step Diffusion with Distribution Matching Distillationcited by 978
  3. 2023Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesiscited by 847
  4. 2023Adversarial Diffusion Distillationcited by 741
  5. 2024Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Thinkcited by 666
  6. 2024Improved Distribution Matching Distillation for Fast Image Synthesiscited by 648
  7. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  8. 2023ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generationcited by 414
  9. 2023InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generationcited by 387
  10. 2023ControlVideo: Training-free Controllable Text-to-Video Generationcited by 324
  11. 2023Ablating Concepts in Text-to-Image Diffusion Modelscited by 312
  12. 2023Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystackcited by 278
38 more
  1. 2024Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillationcited by 276
  2. 2025Diffusion Transformers with Representation Autoencoderscited by 275
  3. 2024SDXL-Lightning: Progressive Adversarial Diffusion Distillationcited by 258
  4. 2023Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioningcited by 254
  5. 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
  6. 2025HPSv3: Towards Wide-Spectrum Human Preference Scorecited by 196
  7. 2023UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANscited by 165
  8. 2023Grounded Text-to-Image Synthesis with Attention Refocusingcited by 163
  9. 2023Raising the Bar of AI-generated Image Detection with CLIPcited by 163
  10. 2023Localizing Object-level Shape Variations with Text-to-Image Diffusion Modelscited by 142
  11. 2025Diffusion Adversarial Post-Training for One-Step Video Generationcited by 142
  12. 2023Intriguing properties of synthetic images: from generative adversarial networks to diffusion modelscited by 121
  13. 2023Taming Encoder for Zero Fine-tuning Image Customization with Text-to-Image Diffusion Modelscited by 116
  14. 2023Anti-DreamBooth: Protecting users from personalized text-to-image synthesiscited by 114
  15. 2024One-Step Image Translation with Text-to-Image Modelscited by 111
  16. 2023SwiftBrush: One-Step Text-to-Image Diffusion Model with Variational Score Distillationcited by 109
  17. 2023Cones 2: Customizable Image Synthesis with Multiple Subjectscited by 101
  18. 2024Arc2Face: A Foundation Model for ID-Consistent Human Facescited by 101
  19. 2023Expressive Text-to-Image Generation with Rich Textcited by 89
  20. 2023Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Modelscited by 85
  21. 2024What If We Recaption Billions of Web Images with LLaMA-3?cited by 82
  22. 2025OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generationcited by 81
  23. 2024Distilling Diffusion Models into Conditional GANscited by 78
  24. 2025What matters for Representation Alignment: Global Information or Spatial Structure?cited by 76
  25. 2023StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editingcited by 68
  26. 2024AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillationcited by 66
  27. 2025AutoPresent: Designing Structured Visuals from Scratchcited by 63
  28. 2023Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Modelscited by 62
  29. 2024Rectified Diffusion: Straightness Is Not Your Need in Rectified Flowcited by 59
  30. 2024PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferencescited by 53
  31. 2024LatentSync: Taming Audio-Conditioned Latent Diffusion Models for Lip Sync with SyncNet Supervisioncited by 53
  32. 2024MagicTime: Time-lapse Video Generation Models as Metamorphic Simulatorscited by 51
  33. 2023Deep Learning Approaches for Data Augmentation in Medical Imaging: A Reviewcited by 48
  34. 2023On the De-duplication of LAION-2Bcited by 47
  35. 2024Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connectionscited by 47
  36. 2024UniPortrait: A Unified Framework for Identity-Preserving Single- and Multi-Human Image Personalizationcited by 46
  37. 2024EG4D: Explicit Generation of 4D Object without Score Distillationcited by 45
  38. 2024SwiftBrush v2: Make Your One-step Diffusion Model Better Than Its Teachercited by 45

50 most cited of 212 All 212 (JSON)

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  1. 2024StyleInject: Parameter Efficient Tuning of Text-to-Image Diffusion Models
  2. 2024Text-to-Image GAN with Pretrained Representations
  3. 2025Weak Supervision Dynamic KL-Weighted Diffusion Models Guided by Large Language Models
  4. 2024E2GAN: Efficient Training of Efficient GANs for Image-to-Image Translation
  5. 2022clip2latent: Text driven sampling of a pre-trained StyleGAN using denoising diffusion and CLIP
  6. 2023Text-driven Visual Synthesis with Latent Diffusion Prior
  7. 2024Text-to-Image Synthesis: A Decade Survey
  8. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model