mlsanityData to 7 Oct 2026

DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis

arXiv 1904.01310 ↗First posted 2 Apr 2019cs.CVcited by 308

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Cited by 105 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper, we focus on generating realistic images from text descriptions. Current methods first generate an initial image with rough shape and color, and then refine the initial image to a high-resolution one. Most existing text-to-image synthesis methods have two main problems. (1) These methods depend heavily on the quality of the initial images. If the initial image is not well initialized, the following processes can hardly refine the image to a satisfactory quality. (2) Each word contributes a different level of importance when depicting different image contents, however, unchanged text representation is used in existing image refinement processes. In this paper, we propose the Dynamic Memory Generative Adversarial Network (DM-GAN) to generate high-quality images. The proposed method introduces a dynamic memory module to refine fuzzy image contents, when the initial images are not well generated. A memory writing gate is designed to select the important text information based on the initial image content, which enables our method to accurately generate images from the text description. We also utilize a response gate to adaptively fuse the information read from the memories and the image features. We evaluate the DM-GAN model on the Caltech-UCSD Birds 200 dataset and the Microsoft Common Objects in Context dataset. Experimental results demonstrate that our DM-GAN model performs favorably against the state-of-the-art approaches.

Key facts. Cited by 308 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2019.

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Citing papers per year: 2021: 42; 2022: 68; 2023: 112; 2024: 57; 2025: 20; 2026: 9.

308 papers.

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  1. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  2. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  3. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  4. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  5. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  6. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,099
  7. 2021Vector Quantized Diffusion Model for Text-to-Image Synthesiscited by 773
  8. 2023MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editingcited by 722
  9. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
  10. 2021CogView: Mastering Text-to-Image Generation via Transformerscited by 691
  11. 2024Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Thinkcited by 666
  12. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 640
38 more
  1. 2023NExT-GPT: Any-to-Any Multimodal LLMcited by 610
  2. 2022All are Worth Words: A ViT Backbone for Diffusion Modelscited by 498
  3. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  4. 2022Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priorscited by 487
  5. 2022Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesiscited by 386
  6. 2023Ablating Concepts in Text-to-Image Diffusion Modelscited by 312
  7. 2022CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformerscited by 305
  8. 2023Composer: Creative and Controllable Image Synthesis with Composable Conditionscited by 303
  9. 2023Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Actioncited by 301
  10. 2021Cross-Modal Contrastive Learning for Text-to-Image Generationcited by 259
  11. 2021N"UWA: Visual Synthesis Pre-training for Neural visUal World creAtioncited by 253
  12. 2023Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translationcited by 253
  13. 2023T2I-CompBench++: An Enhanced and Comprehensive Benchmark for Compositional Text-to-image Generationcited by 253
  14. 2022DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Modelscited by 230
  15. 2021More Control for Free! Image Synthesis with Semantic Diffusion Guidancecited by 211
  16. 2023Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Modelscited by 203
  17. 2023Glaze: Protecting Artists from Style Mimicry by Text-to-Image Modelscited by 200
  18. 2022SINE: SINgle Image Editing with Text-to-Image Diffusion Modelscited by 159
  19. 2023Cache Me if You Can: Accelerating Diffusion Models through Block Cachingcited by 149
  20. 2022CM3: A Causal Masked Multimodal Model of the Internetcited by 142
  21. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Pathscited by 141
  22. 2023Rich Human Feedback for Text-to-Image Generationcited by 139
  23. 2022KNN-Diffusion: Image Generation via Large-Scale Retrievalcited by 135
  24. 2023Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoisingcited by 135
  25. 2021LAFITE: Towards Language-Free Training for Text-to-Image Generationcited by 126
  26. 2024InitNO: Boosting Text-to-Image Diffusion Models via Initial Noise Optimizationcited by 123
  27. 2022ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Expertscited by 110
  28. 2021Paint by Wordcited by 107
  29. 2023Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Modelscited by 98
  30. 2023AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusioncited by 98
  31. 2023HRS-Bench: Holistic, Reliable and Scalable Benchmark for Text-to-Image Modelscited by 94
  32. 2023Improving Tuning-Free Real Image Editing with Proximal Guidancecited by 87
  33. 2023GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesiscited by 84
  34. 2023A-STAR: Test-time Attention Segregation and Retention for Text-to-image Synthesiscited by 78
  35. 2023Ranni: Taming Text-to-Image Diffusion for Accurate Instruction Followingcited by 77
  36. 2022Make-A-Story: Visual Memory Conditioned Consistent Story Generationcited by 76
  37. 2021Multimodal Conditional Image Synthesis with Product-of-Experts GANscited by 75
  38. 2022Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesiscited by 75

50 most cited of 308 All 308 (JSON)