mlsanityData to 14 Oct 2026

ALR-GAN: Adaptive Layout Refinement for Text-to-Image Synthesis

arXiv 2304.06297 ↗First posted 13 Apr 2023cs.CVcited by 4

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Abstract (arXiv)

We propose a novel Text-to-Image Generation Network, Adaptive Layout Refinement Generative Adversarial Network (ALR-GAN), to adaptively refine the layout of synthesized images without any auxiliary information. The ALR-GAN includes an Adaptive Layout Refinement (ALR) module and a Layout Visual Refinement (LVR) loss. The ALR module aligns the layout structure (which refers to locations of objects and background) of a synthesized image with that of its corresponding real image. In ALR module, we proposed an Adaptive Layout Refinement (ALR) loss to balance the matching of hard and easy features, for more efficient layout structure matching. Based on the refined layout structure, the LVR loss further refines the visual representation within the layout area. Experimental results on two widely-used datasets show that ALR-GAN performs competitively at the Text-to-Image generation task.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 33 of its 52 references that are in the map. First posted on arXiv 13 Apr 2023.

Builds on

33 of 52 references.

References · 33

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  12. 2019MirrorGAN: Learning Text-to-image Generation by Redescriptioncited by 176
21 more
  1. 2017Dual-Path Convolutional Image-Text Embeddings with Instance Losscited by 145
  2. 2018StoryGAN: A Sequential Conditional GAN for Story Visualizationcited by 138
  3. 2019Object-driven Text-to-Image Synthesis via Adversarial Trainingcited by 117
  4. 2018Image Generation from Layoutcited by 105
  5. 2018Inferring Semantic Layout for Hierarchical Text-to-Image Synthesiscited by 101
  6. 2019Semantic Object Accuracy for Generative Text-to-Image Synthesiscited by 89
  7. 2019Image Synthesis From Reconfigurable Layout and Stylecited by 85
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  9. 2019Semantics Disentangling for Text-to-Image Generationcited by 61
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  11. 2017Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Modelscited by 53
  12. 2020Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesiscited by 49
  13. 2021DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesiscited by 45
  14. 2019PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graphcited by 44
  15. 2019Generating Multiple Objects at Spatially Distinct Locationscited by 41
  16. 2020Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approachcited by 29
  17. 2017VSE++: Improving Visual-Semantic Embeddings with Hard Negativescited by 21
  18. 2018ChatPainter: Improving Text to Image Generation using Dialoguecited by 18
  19. 2022DR-GAN: Distribution Regularization for Text-to-Image Generationcited by 10
  20. 2019Visual-Relation Conscious Image Generation from Structured-Textcited by 8
  21. 2020Leveraging Visual Question Answering to Improve Text-to-Image Synthesiscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 1.

4 papers.

  1. 2026coDrawAgents: A Multi-Agent Dialogue Framework for Compositional Image Generationcited by 7
  2. 2024Self-supervised Photographic Image Layout Representation Learningcited by 3
  3. 2024TraDiffusion: Trajectory-Based Training-Free Image Generationcited by 2
  4. 2025End-to-end Training for Text-to-Image Synthesis using Dual-Text Embeddingscited by 1