mlsanityData to 7 Oct 2026

Cones 2: Customizable Image Synthesis with Multiple Subjects

arXiv 2305.19327 ↗First posted 30 May 2023cs.CVcited by 101

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Cited by 49 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Synthesizing images with user-specified subjects has received growing attention due to its practical applications. Despite the recent success in single subject customization, existing algorithms suffer from high training cost and low success rate along with increased number of subjects. Towards controllable image synthesis with multiple subjects as the constraints, this work studies how to efficiently represent a particular subject as well as how to appropriately compose different subjects. We find that the text embedding regarding the subject token already serves as a simple yet effective representation that supports arbitrary combinations without any model tuning. Through learning a residual on top of the base embedding, we manage to robustly shift the raw subject to the customized subject given various text conditions. We then propose to employ layout, a very abstract and easy-to-obtain prior, as the spatial guidance for subject arrangement. By rectifying the activations in the cross-attention map, the layout appoints and separates the location of different subjects in the image, significantly alleviating the interference across them. Both qualitative and quantitative experimental results demonstrate our superiority over state-of-the-art alternatives under a variety of settings for multi-subject customization.

Key facts. Cited by 101 papers in the map (data through 7 Oct 2026). Builds on 36 of its 42 references that are in the map. First posted on arXiv 30 May 2023.

Builds on

36 of 42 references.

References · 36

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2022Training language models to follow instructions with human feedbackcited by 15,712
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  7. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  8. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  9. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  10. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  11. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  12. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
24 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. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,961
  4. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,339
  5. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,287
  6. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,099
  7. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
  8. 2021CogView: Mastering Text-to-Image Generation via Transformerscited by 691
  9. 2023Zero-shot Image-to-Image Translationcited by 503
  10. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  11. 2022Paint by Example: Exemplar-based Image Editing with Diffusion Modelscited by 489
  12. 2022Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priorscited by 487
  13. 2023ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generationcited by 414
  14. 2022Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesiscited by 386
  15. 2023Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Modelscited by 358
  16. 2022Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Modelscited by 331
  17. 2023Composer: Creative and Controllable Image Synthesis with Composable Conditionscited by 303
  18. 2023StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesiscited by 212
  19. 2023Subject-driven Text-to-Image Generation via Apprenticeship Learningcited by 210
  20. 2023Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Modelscited by 203
  21. 2023Cones: Concept Neurons in Diffusion Models for Customized Generationcited by 150
  22. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Pathscited by 141
  23. 2015Generating Images from Captions with Attentioncited by 135
  24. 2023GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesiscited by 84

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 14; 2024: 53; 2025: 28; 2026: 6.

101 papers.

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  1. 2025VACE: All-in-One Video Creation and Editingcited by 467
  2. 2023AnyDoor: Zero-shot Object-level Image Customizationcited by 411
  3. 2023PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embeddingcited by 324
  4. 2023Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuningcited by 191
  5. 2023DreamVideo: Composing Your Dream Videos with Customized Subject and Motioncited by 186
  6. 2024MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidancecited by 142
  7. 2024GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editingcited by 132
  8. 2023VideoBooth: Diffusion-based Video Generation with Image Promptscited by 124
  9. 2024UniReal: Universal Image Generation and Editing via Learning Real-world Dynamicscited by 100
  10. 2024MotionBooth: Motion-Aware Customized Text-to-Video Generationcited by 92
  11. 2024Controllable Generation with Text-to-Image Diffusion Models: A Surveycited by 82
  12. 2024CustomVideo: Customizing Text-to-Video Generation with Multiple Subjectscited by 76
38 more
  1. 2024OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Modelscited by 64
  2. 2024Zero-shot Image Editing with Reference Imitationcited by 64
  3. 2024DreamMatcher: Appearance Matching Self-Attention for Semantically-Consistent Text-to-Image Personalizationcited by 60
  4. 2024Magic-Me: Identity-Specific Video Customized Diffusioncited by 58
  5. 2024LoRA-Composer: Leveraging Low-Rank Adaptation for Multi-Concept Customization in Training-Free Diffusion Modelscited by 55
  6. 2024λ-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent Spacecited by 51
  7. 2024FreeCustom: Tuning-Free Customized Image Generation for Multi-Concept Compositioncited by 49
  8. 2024UniPortrait: A Unified Framework for Identity-Preserving Single- and Multi-Human Image Personalizationcited by 46
  9. 2024MultiBooth: Towards Generating All Your Concepts in an Image from Textcited by 45
  10. 2023LivePhoto: Real Image Animation with Text-guided Motion Controlcited by 44
  11. 2024DreamVideo-2: Zero-Shot Subject-Driven Video Customization with Precise Motion Controlcited by 42
  12. 2024RealCustom: Narrowing Real Text Word for Real-Time Open-Domain Text-to-Image Customizationcited by 39
  13. 2023AutoStory: Generating Diverse Storytelling Images with Minimal Human Effortcited by 38
  14. 2024StableIdentity: Inserting Anybody into Anywhere at First Sightcited by 35
  15. 2024Identity Decoupling for Multi-Subject Personalization of Text-to-Image Modelscited by 33
  16. 2024SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Controlcited by 32
  17. 2024How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization?cited by 32
  18. 2024FlashFace: Human Image Personalization with High-fidelity Identity Preservationcited by 31
  19. 2024MagicQuill: An Intelligent Interactive Image Editing Systemcited by 30
  20. 2023R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generationcited by 29
  21. 2024A Survey on Personalized Content Synthesis with Diffusion Modelscited by 29
  22. 2024Conditional Image Synthesis with Diffusion Models: A Surveycited by 29
  23. 2025Movie Weaver: Tuning-Free Multi-Concept Video Personalization with Anchored Promptscited by 28
  24. 2023Degeneration-Tuning: Using Scrambled Grid shield Unwanted Concepts from Stable Diffusioncited by 27
  25. 2024MC2: Multi-concept Guidance for Customized Multi-concept Generationcited by 26
  26. 2024CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Modelscited by 24
  27. 2024Magic Clothing: Controllable Garment-Driven Image Synthesiscited by 23
  28. 2024Group Diffusion Transformers are Unsupervised Multitask Learnerscited by 22
  29. 2025Personalize Anything for Free with Diffusion Transformercited by 22
  30. 2023LoCo: Locally Constrained Training-Free Layout-to-Image Synthesiscited by 21
  31. 2025Personalized Image Generation with Deep Generative Models: A Decade Surveycited by 20
  32. 2025MangaNinja: Line Art Colorization with Precise Reference Followingcited by 17
  33. 2024Learning Continuous 3D Words for Text-to-Image Generationcited by 16
  34. 2024RealCustom++: Representing Images as Real Textual Word for Real-Time Customizationcited by 16
  35. 2025AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generationcited by 16
  36. 2023CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalizationcited by 15
  37. 2024Non-confusing Generation of Customized Concepts in Diffusion Modelscited by 15
  38. 2024Doubly Abductive Counterfactual Inference for Text-based Image Editingcited by 12

50 most cited of 101 All 101 (JSON)