mlsanityData to 7 Oct 2026

Semantics Disentangling for Text-to-Image Generation

arXiv 1904.01480 ↗First posted 2 Apr 2019cs.CVcited by 61

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Abstract (arXiv)

Synthesizing photo-realistic images from text descriptions is a challenging problem. Previous studies have shown remarkable progresses on visual quality of the generated images. In this paper, we consider semantics from the input text descriptions in helping render photo-realistic images. However, diverse linguistic expressions pose challenges in extracting consistent semantics even they depict the same thing. To this end, we propose a novel photo-realistic text-to-image generation model that implicitly disentangles semantics to both fulfill the high-level semantic consistency and low-level semantic diversity. To be specific, we design (1) a Siamese mechanism in the discriminator to learn consistent high-level semantics, and (2) a visual-semantic embedding strategy by semantic-conditioned batch normalization to find diverse low-level semantics. Extensive experiments and ablation studies on CUB and MS-COCO datasets demonstrate the superiority of the proposed method in comparison to state-of-the-art methods.

Key facts. Cited by 61 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: 17; 2022: 15; 2023: 18; 2024: 5; 2025: 4; 2026: 2.

61 papers.

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  1. 2021Vector Quantized Diffusion Model for Text-to-Image Synthesiscited by 773
  2. 2021Cross-Modal Contrastive Learning for Text-to-Image Generationcited by 259
  3. 2021Paint by Wordcited by 107
  4. 2023GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesiscited by 84
  5. 2022Make-A-Story: Visual Memory Conditioned Consistent Story Generationcited by 76
  6. 2022StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuationcited by 74
  7. 2023Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generationcited by 66
  8. 2021Improving Text-to-Image Synthesis Using Contrastive Learningcited by 62
  9. 2022CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIPcited by 60
  10. 2021Text to Image Generation with Semantic-Spatial Aware GANcited by 53
  11. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  12. 2021Multimodal Image Synthesis and Editing: The Generative AI Eracited by 52
38 more
  1. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Modelcited by 47
  2. 2023Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Modelscited by 40
  3. 2022StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesiscited by 33
  4. 2023High-Fidelity 3D Face Generation from Natural Language Descriptionscited by 32
  5. 2021Cycle-Consistent Inverse GAN for Text-to-Image Synthesiscited by 27
  6. 2023GlueGen: Plug and Play Multi-modal Encoders for X-to-image Generationcited by 25
  7. 2024Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertaintycited by 23
  8. 2023Attribute-Centric Compositional Text-to-Image Generationcited by 19
  9. 2022FEAT: Face Editing with Attentioncited by 16
  10. 2023CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalizationcited by 15
  11. 2021TISE: Bag of Metrics for Text-to-Image Synthesis Evaluationcited by 13
  12. 2022DSE-GAN: Dynamic Semantic Evolution Generative Adversarial Network for Text-to-Image Generationcited by 13
  13. 2024PartCraft: Crafting Creative Objects by Partscited by 13
  14. 2021CRD-CGAN: Category-Consistent and Relativistic Constraints for Diverse Text-to-Image Generationcited by 10
  15. 2022DR-GAN: Distribution Regularization for Text-to-Image Generationcited by 10
  16. 2022Layout-Bridging Text-to-Image Synthesiscited by 9
  17. 2021Deep Image Synthesis from Intuitive User Input: A Review and Perspectivescited by 8
  18. 2023Vision + Language Applications: A Surveycited by 8
  19. 2021DiverGAN: An Efficient and Effective Single-Stage Framework for Diverse Text-to-Image Generationcited by 7
  20. 2022AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal Generationcited by 7
  21. 2022Adma-GAN: Attribute-Driven Memory Augmented GANs for Text-to-Image Generationcited by 6
  22. 2023Fine-grained Cross-modal Fusion based Refinement for Text-to-Image Synthesiscited by 6
  23. 2022Vision-Language Matching for Text-to-Image Synthesis via Generative Adversarial Networkscited by 5
  24. 2023DreamCreature: Crafting Photorealistic Virtual Creatures from Imaginationcited by 5
  25. 2024Text-to-Image Cross-Modal Generation: A Systematic Reviewcited by 5
  26. 2022Understanding Attention for Vision-and-Language Taskscited by 4
  27. 2022T-Person-GAN: Text-to-Person Image Generation with Identity-Consistency and Manifold Mix-Upcited by 4
  28. 2023ALR-GAN: Adaptive Layout Refinement for Text-to-Image Synthesiscited by 4
  29. 2023T2IW: Joint Text to Image & Watermark Generationcited by 4
  30. 2026Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamics Mechanisms and Efficient Alignmentcited by 4
  31. 2023MatchXML: An Efficient Text-label Matching Framework for Extreme Multi-label Text Classificationcited by 3
  32. 2021CAGAN: Text-To-Image Generation with Combined Attention GANscited by 2
  33. 2022T2CI-GAN: Text to Compressed Image generation using Generative Adversarial Networkcited by 2
  34. 2023Fusion-S2iGan: An Efficient and Effective Single-Stage Framework for Speech-to-Image Generationcited by 2
  35. 2021Fine-Grained Image Generation from Bangla Text Description using Attentional Generative Adversarial Networkcited by 1
  36. 2021Each Attribute Matters: Contrastive Attention for Sentence-based Image Editingcited by 1
  37. 2023The Right Losses for the Right Gains: Improving the Semantic Consistency of Deep Text-to-Image Generation with Distribution-Sensitive Lossescited by 1
  38. 2024ArtiFade: Learning to Generate High-quality Subject from Blemished Imagescited by 1

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