mlsanityData to 7 Oct 2026

AccDiffusion: An Accurate Method for Higher-Resolution Image Generation

arXiv 2407.10738 ↗First posted 15 Jul 2024cs.CVcited by 32

Not on the map. Why?

Cited by 25 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This paper attempts to address the object repetition issue in patch-wise higher-resolution image generation. We propose AccDiffusion, an accurate method for patch-wise higher-resolution image generation without training. An in-depth analysis in this paper reveals an identical text prompt for different patches causes repeated object generation, while no prompt compromises the image details. Therefore, our AccDiffusion, for the first time, proposes to decouple the vanilla image-content-aware prompt into a set of patch-content-aware prompts, each of which serves as a more precise description of an image patch. Besides, AccDiffusion also introduces dilated sampling with window interaction for better global consistency in higher-resolution image generation. Experimental comparison with existing methods demonstrates that our AccDiffusion effectively addresses the issue of repeated object generation and leads to better performance in higher-resolution image generation.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). Builds on 30 of its 34 references that are in the map. First posted on arXiv 15 Jul 2024.

Builds on

30 of 34 references.

References · 30

  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. 2020Denoising Diffusion Implicit Modelscited by 9,655
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  6. 2023Segment Anythingcited by 8,158
  7. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  8. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  9. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  10. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  11. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  12. 2016Improved Techniques for Training GANscited by 2,938
18 more
  1. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  2. 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,765
  3. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
  4. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  5. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
  6. 2023MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generationcited by 529
  7. 2021Designing a Practical Degradation Model for Deep Blind Image Super-Resolutioncited by 524
  8. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolutioncited by 486
  9. 2023Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Modelscited by 323
  10. 2022Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Modelscited by 151
  11. 2023Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Modelcited by 145
  12. 2023ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Modelscited by 127
  13. 2023SyncDiffusion: Coherent Montage via Synchronized Joint Diffusionscited by 108
  14. 2023DemoFusion: Democratising High-Resolution Image Generation With No cited by 105
  15. 2023DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuningcited by 82
  16. 2022Any-resolution Training for High-resolution Image Synthesiscited by 72
  17. 2023Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesiscited by 55
  18. 2023Any-Size-Diffusion: Toward Efficient Text-Driven Synthesis for Any-Size HD Imagescited by 36

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 15; 2026: 9.

32 papers.

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  1. 2024LinFusion: 1 GPU, 1 Minute, 16K Imagecited by 42
  2. 2024FreeScale: Unleashing the Resolution of Diffusion Models via Tuning-Free Scale Fusioncited by 29
  3. 2025Latent Space Super-Resolution for Higher-Resolution Image Generation with Diffusion Modelscited by 24
  4. 2024I-Max: Maximize the Resolution Potential of Pre-trained Rectified Flow Transformers with Projected Flowcited by 21
  5. 2024FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded Samplingcited by 15
  6. 2024HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM Promptscited by 14
  7. 2025DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusioncited by 13
  8. 2024FAM Diffusion: Frequency and Attention Modulation for High-Resolution Image Generation with Stable Diffusioncited by 12
  9. 2025HiStream: Efficient High-Resolution Video Generation via Redundancy-Eliminated Streamingcited by 8
  10. 2024RepLDM: Reprogramming Pretrained Latent Diffusion Models for High-Quality, High-Efficiency, High-Resolution Image Generationcited by 6
  11. 2025LightMotion: A Light and Tuning-free Method for Simulating Camera Motion in Video Generationcited by 5
  12. 2025HiWave: Training-Free High-Resolution Image Generation via Wavelet-Based Diffusion Samplingcited by 5
20 more
  1. 2025ScaleDiff: Higher-Resolution Image Synthesis via Efficient and Model-Agnostic Diffusioncited by 5
  2. 2025Parallel Sequence Modeling via Generalized Spatial Propagation Networkcited by 4
  3. 2026Extend3D: Town-Scale 3D Generationcited by 4
  4. 2024AccDiffusion v2: Towards More Accurate Higher-Resolution Diffusion Extrapolationcited by 3
  5. 2025Exploring Position Encoding in Diffusion U-Net for Training-free High-resolution Image Generationcited by 3
  6. 2025Creatively Upscaling Images with Global-Regional Priorscited by 2
  7. 2026SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformerscited by 2
  8. 2025RectifiedHR: Enable Efficient High-Resolution Synthesis via Energy Rectificationcited by 1
  9. 2025InfoScale: Unleashing Training-free Variable-scaled Image Generation via Effective Utilization of Informationcited by 1
  10. 2025ResDiT: Evoking the Intrinsic Resolution Scalability in Diffusion Transformerscited by 1
  11. 2026PixelRush: Ultra-Fast, Training-Free High-Resolution Image Generation via One-step Diffusioncited by 1
  12. 2025APT: Improving Diffusion Models for High Resolution Image Generation with Adaptive Path Tracingcited by 0
  13. 2025TIDE: Achieving Balanced Subject-Driven Image Generation via Target-Instructed Diffusion Enhancementcited by 0
  14. 2025HaineiFRDM: Structure-Preserving Diffusion for Film Restoration under Fast Motion and Diverse Defectscited by 0
  15. 2026InfScene-SR: Seamless Super-Resolution of Arbitrarily Large Remote-Sensing Scenes via Variance-Preserving Joint Denoisingcited by 0
  16. 2026Supersampling Stable Diffusion and Beyond: A Seamless, Training-Free Approach for Scaling Neural Networks Using Common Interpolation Methodscited by 0
  17. 2026PhotoQuilt: Training-Free Arbitrary-Resolution Photomosaics via Bootstrapped Tiled Denoisingcited by 0
  18. 2026Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editingcited by 0
  19. 2026HRDiT: Training-Free High-Resolution Image Generation with Off-the-Shelf Diffusion Transformer Modelscited by 0
  20. 2026JoLT: Joint Latent Trajectories for Context-Guided High-Resolution Tiled Generationcited by 0