mlsanityData to 14 Oct 2026

Training-Free Location-Aware Text-to-Image Synthesis

arXiv 2304.13427 ↗First posted 26 Apr 2023cs.CVcited by 13

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Abstract (arXiv)

Current large-scale generative models have impressive efficiency in generating high-quality images based on text prompts. However, they lack the ability to precisely control the size and position of objects in the generated image. In this study, we analyze the generative mechanism of the stable diffusion model and propose a new interactive generation paradigm that allows users to specify the position of generated objects without additional training. Moreover, we propose an object detection-based evaluation metric to assess the control capability of location aware generation task. Our experimental results show that our method outperforms state-of-the-art methods on both control capacity and image quality.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 17 of its 20 references that are in the map. First posted on arXiv 26 Apr 2023.

Builds on

17 of 20 references.

References · 17

  1. 2017Attention Is All You Needcited by 60,361
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  5. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  6. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  7. 2020Denoising Diffusion Implicit Modelscited by 9,781
  8. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  9. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  10. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  11. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
  12. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,431
5 more
  1. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,178
  2. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 931
  3. 2022Compositional Visual Generation with Composable Diffusion Modelscited by 624
  4. 2022Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesiscited by 388
  5. 2021You Only Learn One Representation: Unified Network for Multiple Taskscited by 86

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 5; 2025: 1; 2026: 2.

13 papers.

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  1. 2024StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generationcited by 247
  2. 2023Guided Image Synthesis via Initial Image Editing in Diffusion Modelcited by 63
  3. 2023A Survey of Diffusion Based Image Generation Models: Issues and Their Solutionscited by 25
  4. 2024NoiseCollage: A Layout-Aware Text-to-Image Diffusion Model Based on Noise Cropping and Mergingcited by 25
  5. 2023The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initializationcited by 23
  6. 2023MaskDiffusion: Boosting Text-to-Image Consistency with Conditional Maskcited by 17
  7. 2023Predicated Diffusion: Predicate Logic-Based Attention Guidance for Text-to-Image Diffusion Modelscited by 16
  8. 2024Training-Free Sketch-Guided Diffusion with Latent Optimizationcited by 7
  9. 2024Isolated Diffusion: Optimizing Multi-Concept Text-to-Image Generation Training-Freely with Isolated Diffusion Guidancecited by 6
  10. 2024Layout-to-Image Generation with Localized Descriptions using ControlNet with Cross-Attention Controlcited by 5
  11. 2025Geometrical Properties of Text Token Embeddings for Strong Semantic Binding in Text-to-Image Generationcited by 5
  12. 2026LGTM: Training-Free Light-Guided Text-to-Image Diffusion Model via Initial Noise Manipulationcited by 1
1 more
  1. 2026Appearance Pointers -- Multimodal Region Control of Diffusion Transformerscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
  2. 2024ST-LDM: A Universal Framework for Text-Grounded Object Generation in Real Images
  3. 2025A Two-Stage System for Layout-Controlled Image Generation using Large Language Models and Diffusion Models
  4. 2024Training-free Composite Scene Generation for Layout-to-Image Synthesis
  5. 2024Prompt-Consistency Image Generation (PCIG): A Unified Framework Integrating LLMs, Knowledge Graphs, and Controllable Diffusion Models
  6. 2023R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation
  7. 2023Text-to-image Diffusion Models in Generative AI: A Survey
  8. 2025Grounding Text-to-Image Diffusion Models for Controlled High-Quality Image Generation