mlsanityData to 7 Oct 2026

ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation

arXiv 2502.09411 ↗First posted 13 Feb 2025cs.CV cs.GRcited by 20

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

Diffusion models enable high-quality and diverse visual content synthesis. However, they struggle to generate rare or unseen concepts. To address this challenge, we explore the usage of Retrieval-Augmented Generation (RAG) with image generation models. We propose ImageRAG, a method that dynamically retrieves relevant images based on a given text prompt, and uses them as context to guide the generation process. Prior approaches that used retrieved images to improve generation, trained models specifically for retrieval-based generation. In contrast, ImageRAG leverages the capabilities of existing image conditioning models, and does not require RAG-specific training. Our approach is highly adaptable and can be applied across different model types, showing significant improvement in generating rare and fine-grained concepts using different base models. Our project page is available at: https://rotem-shalev.github.io/ImageRAG

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 61 of its 79 references that are in the map. First posted on arXiv 13 Feb 2025.

Builds on

61 of 79 references.

Closest ancestors · 18

Same direction, newest first

  1. 2025RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning2 Feb
  2. 2024GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis8 Dec
  3. 2024OmniGen: Unified Image Generation17 Sep
  4. 2024Analogist: Out-of-the-box Visual In-Context Learning with Image Diffusion Model16 May
  5. 2024Lazy Diffusion Transformer for Interactive Image Editing18 Apr
  6. 2024Block-wise LoRA: Revisiting Fine-grained LoRA for Effective Personalization and Stylization in Text-to-Image Generation12 Mar
  7. 2024InstantID: Zero-shot Identity-Preserving Generation in Seconds15 Jan
  8. 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models13 Aug
  9. 2023Norm-guided latent space exploration for text-to-image generation14 Jun
  10. 2023In-Context Learning Unlocked for Diffusion Models1 May
  11. 2023Generating images of rare concepts using pre-trained diffusion models27 Apr
  12. 2023Adding Conditional Control to Text-to-Image Diffusion Models10 Feb
6 more
  1. 2022Multi-Concept Customization of Text-to-Image Diffusion8 Dec
  2. 2022SpaText: Spatio-Textual Representation for Controllable Image Generation25 Nov
  3. 2022InstructPix2Pix: Learning to Follow Image Editing Instructions17 Nov
  4. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Models17 Nov
  5. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation25 Aug
  6. 2021Blended Diffusion for Text-driven Editing of Natural Images29 Nov

Other references · 43

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  7. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  8. 2023Visual Instruction Tuningcited by 7,792
  9. 2024GPT-4o System Cardcited by 4,467
  10. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  11. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  12. 2023Sigmoid Loss for Language Image Pre-Trainingcited by 3,048
31 more
  1. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  2. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  3. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  4. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  5. 2013Fine-Grained Visual Classification of Aircraftcited by 1,701
  6. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,306
  7. 2021Improving language models by retrieving from trillions of tokenscited by 1,278
  8. 2023In-Context Retrieval-Augmented Language Modelscited by 694
  9. 2023MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Actioncited by 511
  10. 2023Generative Multimodal Models are In-Context Learnerscited by 446
  11. 2024OminiControl: Minimal and Universal Control for Diffusion Transformercited by 334
  12. 2023P+: Extended Textual Conditioning in Text-to-Image Generationcited by 242
  13. 2023Break-A-Scene: Extracting Multiple Concepts from a Single Imagecited by 230
  14. 2022Re-Imagen: Retrieval-Augmented Text-to-Image Generatorcited by 208
  15. 2023Teaching CLIP to Count to Tencited by 194
  16. 2021Fine-Grained Image Analysis with Deep Learning: A Surveycited by 135
  17. 2022KNN-Diffusion: Image Generation via Large-Scale Retrievalcited by 135
  18. 2024GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editingcited by 132
  19. 2024DreamBench++: A Human-Aligned Benchmark for Personalized Image Generationcited by 131
  20. 2023A Neural Space-Time Representation for Text-to-Image Personalizationcited by 123
  21. 2024Instruct-Imagen: Image Generation with Multi-modal Instructioncited by 65
  22. 2023COLA: A Benchmark for Compositional Text-to-image Retrievalcited by 53
  23. 2024PALP: Prompt Aligned Personalization of Text-to-Image Modelscited by 35
  24. 2024INQUIRE: A Natural World Text-to-Image Retrieval Benchmarkcited by 33
  25. 2023Context Diffusion: In-Context Aware Image Generationcited by 20
  26. 2025Towards AI-driven Sign Language Generation with Non-manual Markerscited by 13
  27. 2024AttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generationcited by 10
  28. 2024FineDiffusion: Scaling up Diffusion Models for Fine-grained Image Generation with 10,000 Classescited by 5
  29. 2024BRIEF: Bridging Retrieval and Inference for Multi-hop Reasoning via Compressioncited by 5
  30. 2024Not Every Image is Worth a Thousand Words: Quantifying Originality in Stable Diffusioncited by 4
  31. 2024Efficient and Interpretable Information Retrieval for Product Question Answering with Heterogeneous Datacited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 11; 2026: 9.

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  1. 2025Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlookcited by 32
  2. 2025A Survey of Personalization: From RAG to Agentcited by 26
  3. 2025UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularitiescited by 18
  4. 2025MotionRAG: Motion Retrieval-Augmented Image-to-Video Generationcited by 7
  5. 2025BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactionscited by 4
  6. 2025ImageSentinel: Protecting Visual Datasets from Unauthorized Retrieval-Augmented Image Generationcited by 4
  7. 2025RefVNLI: Towards Scalable Evaluation of Subject-driven Text-to-image Generationcited by 3
  8. 2025Chain-of-Cooking:Cooking Process Visualization via Bidirectional Chain-of-Thought Guidancecited by 3
  9. 2025Attribution-by-design: Ensuring Inference-Time Provenance in Generative Music Systemscited by 3
  10. 2026ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generationcited by 3
  11. 2025Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environmentcited by 1
  12. 2026SAR-RAG: ATR Visual Question Answering by Semantic Search, Retrieval, and MLLM Generationcited by 1
8 more
  1. 2025MV-RAG: Retrieval Augmented Multiview Diffusioncited by 0
  2. 2026Visual Personalization Turing Testcited by 0
  3. 2026FarmMind: Reasoning-Query-Driven Dynamic Segmentation for Farmland Remote Sensing Imagescited by 0
  4. 2026ImageRAGTurbo: Towards One-step Text-to-Image Generation with Retrieval-Augmented Diffusion Modelscited by 0
  5. 2026ASTRA: Enhancing Multi-Subject Generation with Retrieval-Augmented Pose Guidance and Disentangled Position Embeddingcited by 0
  6. 2026ImageAuditor: Membership Inference Attack against Image-based Retrieval-Augmented Generationcited by 0
  7. 2026Agentic Visual Generation: From Generative Models to Agentic Controlcited by 0
  8. 2026Memory-Guided B-Roll Generation from User Video Collectionscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models
  2. 2025VideoRAG: Retrieval-Augmented Generation over Video Corpus
  3. 2025Visual-RAG: Benchmarking Text-to-Image Retrieval Augmented Generation for Visual Knowledge Intensive Queries
  4. 2024PQPP: A Joint Benchmark for Text-to-Image Prompt and Query Performance Prediction
  5. 2025RegionRAG: Region-level Retrieval-Augmented Generation for Visual Document Understanding
  6. 2025AR-RAG: Autoregressive Retrieval Augmentation for Image Generation
  7. 2024Searching for Best Practices in Retrieval-Augmented Generation
  8. 2025Cross-modal RAG: Sub-dimensional Text-to-Image Retrieval-Augmented Generation