mlsanityData to 14 Oct 2026

Object-driven Text-to-Image Synthesis via Adversarial Training

arXiv 1902.10740 ↗First posted 27 Feb 2019cs.CVcited by 117

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Cited by 24 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper, we propose Object-driven Attentive Generative Adversarial Newtorks (Obj-GANs) that allow object-centered text-to-image synthesis for complex scenes. Following the two-step (layout-image) generation process, a novel object-driven attentive image generator is proposed to synthesize salient objects by paying attention to the most relevant words in the text description and the pre-generated semantic layout. In addition, a new Fast R-CNN based object-wise discriminator is proposed to provide rich object-wise discrimination signals on whether the synthesized object matches the text description and the pre-generated layout. The proposed Obj-GAN significantly outperforms the previous state of the art in various metrics on the large-scale COCO benchmark, increasing the Inception score by 27% and decreasing the FID score by 11%. A thorough comparison between the traditional grid attention and the new object-driven attention is provided through analyzing their mechanisms and visualizing their attention layers, showing insights of how the proposed model generates complex scenes in high quality.

Key facts. Cited by 117 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Feb 2019.

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Citing papers per year: 2021: 34; 2022: 40; 2023: 30; 2024: 7; 2025: 3; 2026: 3.

117 papers.

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  1. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  2. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
  3. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,431
  4. 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 991
  5. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 927
  6. 2023GLIGEN: Open-Set Grounded Text-to-Image Generationcited by 781
  7. 2021Vector Quantized Diffusion Model for Text-to-Image Synthesiscited by 774
  8. 2021CogView: Mastering Text-to-Image Generation via Transformerscited by 694
  9. 2023InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generationcited by 395
  10. 2021Cross-Modal Contrastive Learning for Text-to-Image Generationcited by 259
  11. 2022SpaText: Spatio-Textual Representation for Controllable Image Generationcited by 217
  12. 2023Glaze: Protecting Artists from Style Mimicry by Text-to-Image Modelscited by 205
38 more
  1. 2022ReCo: Region-Controlled Text-to-Image Generationcited by 179
  2. 2022DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Modelscited by 168
  3. 2021Illiterate DALL-E Learns to Composecited by 147
  4. 2023VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planningcited by 141
  5. 2021LAFITE: Towards Language-Free Training for Text-to-Image Generationcited by 128
  6. 2023Collaborative Diffusion for Multi-Modal Face Generation and Editingcited by 116
  7. 2021Paint by Wordcited by 107
  8. 2023GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesiscited by 85
  9. 2022Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesiscited by 75
  10. 2023TaleCrafter: Interactive Story Visualization with Multiple Characterscited by 73
  11. 2021FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizationcited by 71
  12. 2023Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generationcited by 68
  13. 2021Improving Text-to-Image Synthesis Using Contrastive Learningcited by 62
  14. 2022CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIPcited by 60
  15. 2023Unified Multi-Modal Latent Diffusion for Joint Subject and Text Conditional Image Generationcited by 60
  16. 2023Shape-aware Text-driven Layered Video Editingcited by 54
  17. 2023Visual Programming for Text-to-Image Generation and Evaluationcited by 54
  18. 2021Text to Image Generation with Semantic-Spatial Aware GANcited by 53
  19. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  20. 2021Multimodal Image Synthesis and Editing: The Generative AI Eracited by 52
  21. 2022Discover and Mitigate Unknown Biases with Debiasing Alternate Networkscited by 47
  22. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Modelcited by 47
  23. 2021DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesiscited by 45
  24. 2021Improving Generation and Evaluation of Visual Stories via Semantic Consistencycited by 43
  25. 2022Modeling Image Composition for Complex Scene Generationcited by 43
  26. 2022SceneComposer: Any-Level Semantic Image Synthesiscited by 43
  27. 2023Highly Personalized Text Embedding for Image Manipulation by Stable Diffusioncited by 39
  28. 2021Multimodal Dialogue Response Generationcited by 32
  29. 2023Gradient-Free Textual Inversioncited by 29
  30. 2022Vision-Language Intelligence: Tasks, Representation Learning, and Large Modelscited by 28
  31. 2021Cycle-Consistent Inverse GAN for Text-to-Image Synthesiscited by 27
  32. 2023Multi-modal Machine Learning in Engineering Design: A Review and Future Directionscited by 27
  33. 2022One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulationscited by 24
  34. 2023Generative Watermarking Against Unauthorized Subject-Driven Image Synthesiscited by 23
  35. 2022Vision+X: A Survey on Multimodal Learning in the Light of Datacited by 22
  36. 2024Generative Multi-modal Models are Good Class-Incremental Learnerscited by 22
  37. 2024LEDiff: Latent Exposure Diffusion for HDR Generationcited by 22
  38. 2024Bi-LORA: A Vision-Language Approach for Synthetic Image Detectioncited by 20

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