mlsanityData to 7 Oct 2026

Tutorial on Diffusion Models for Imaging and Vision

arXiv 2403.18103 ↗First posted 26 Mar 2024cs.LG cs.CVcited by 49

On the map: Diffusion models → Diffusion foundations and sampling

Abstract (arXiv)

The astonishing growth of generative tools in recent years has empowered many exciting applications in text-to-image generation and text-to-video generation. The underlying principle behind these generative tools is the concept of diffusion, a particular sampling mechanism that has overcome some shortcomings that were deemed difficult in the previous approaches. The goal of this tutorial is to discuss the essential ideas underlying the diffusion models. The target audience of this tutorial includes undergraduate and graduate students who are interested in doing research on diffusion models or applying these models to solve other problems.

Key facts. Cited by 49 papers in the map (data through 7 Oct 2026). Placed in Diffusion foundations and sampling, one of 14 directions in Diffusion models. Builds on 23 of its 46 references that are in the map. First posted on arXiv 26 Mar 2024.

Builds on

23 of 46 references.

Closest ancestors · 9

Same direction, newest first

  1. 2022On Distillation of Guided Diffusion Models6 Oct
  2. 2022Understanding Diffusion Models: A Unified Perspective25 Aug
  3. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps2 Jun
  4. 2022Elucidating the Design Space of Diffusion-Based Generative Models1 Jun
  5. 2022Progressive Distillation for Fast Sampling of Diffusion Models1 Feb
  6. 2021High-Resolution Image Synthesis with Latent Diffusion Models20 Dec
  7. 2021Variational Diffusion Models1 Jul
  8. 2020Denoising Diffusion Probabilistic Models19 Jun
  9. 2020Improved Techniques for Training Score-Based Generative Models16 Jun

Other references · 14

  1. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  2. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  3. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  4. 2015Variational Inference with Normalizing Flowscited by 2,161
  5. 2019An Introduction to Variational Autoencoderscited by 997
  6. 2022Denoising Diffusion Restoration Modelscited by 951
  7. 2023Stochastic Interpolants: A Unifying Framework for Flows and Diffusionscited by 897
  8. 2016Tutorial on Variational Autoencoderscited by 404
  9. 2021Score-based diffusion models for accelerated MRIcited by 308
  10. 2016Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applicationscited by 244
  11. 2020Solving Linear Inverse Problems Using the Prior Implicit in a Denoisercited by 78
  12. 2014Generative Adversarial Networkscited by 25
2 more
  1. 2023Generative Plug and Play: Posterior Sampling for Inverse Problemscited by 24
  2. 2023Kernel Diffusion: An Alternate Approach to Blind Deconvolutioncited by 13

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 16; 2025: 25; 2026: 8.

49 papers.

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  1. 2024Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusioncited by 634
  2. 2024Diffusion Policy Policy Optimizationcited by 255
  3. 2025History-Guided Video Diffusioncited by 165
  4. 2024How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Frameworkcited by 48
  5. 2024Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexitycited by 42
  6. 2024Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learningcited by 35
  7. 2024Generative Photography: Scene-Consistent Camera Control for Realistic Text-to-Image Synthesiscited by 26
  8. 2024Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Surveycited by 23
  9. 2025Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approachcited by 18
  10. 2024Poisson Variational Autoencodercited by 11
  11. 2024Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstructioncited by 9
  12. 2024Bridging SFT and DPO for Diffusion Model Alignment with Self-Sampling Preference Optimizationcited by 8
37 more
  1. 2024Pixel-Space Post-Training of Latent Diffusion Modelscited by 6
  2. 2024Random Walks with Tweedie: A Unified View of Score-Based Diffusion Modelscited by 6
  3. 2025SimFlow: Simplified and End-to-End Training of Latent Normalizing Flowscited by 6
  4. 2026Flow Equivariant World Models: Memory for Partially Observed Dynamic Environmentscited by 6
  5. 2024Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Datacited by 5
  6. 2025Clustering via Self-Supervised Diffusioncited by 3
  7. 2025RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Modelscited by 3
  8. 2025Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solverscited by 2
  9. 2025SPIEDiff: robust learning of long-time macroscopic dynamics from short-time particle simulations with quantified epistemic uncertaintycited by 2
  10. 2025DiffPF: Differentiable Particle Filtering with Generative Sampling via Conditional Diffusion Modelscited by 2
  11. 2026ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillationcited by 2
  12. 2024A Deep Generative Framework for Joint Households and Individuals Population Synthesiscited by 1
  13. 2025DnD Filter: Differentiable State Estimation for Dynamic Systems using Diffusion Modelscited by 1
  14. 2025Preserve and Personalize: Personalized Text-to-Image Diffusion Models without Distributional Driftcited by 1
  15. 2025DiffVolume: Diffusion Models for Volume Generation in Limit Order Bookscited by 1
  16. 2025A Frequentist Statistical Introduction to Variational Inference, Autoencoders, and Diffusion Modelscited by 1
  17. 2025Is Your Conditional Diffusion Model Actually Denoising?cited by 1
  18. 2026A Gibbs posterior sampler for inverse problem based on prior diffusion modelcited by 1
  19. 2024IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer Studycited by 0
  20. 2024Diffusion Model from Scratchcited by 0
  21. 2025Advancing MRI Reconstruction: A Systematic Review of Deep Learning and Compressed Sensing Integrationcited by 0
  22. 2025Compact Latent Representation for Image Compression (CLRIC)cited by 0
  23. 2025DiffBrush:Just Painting the Art by Your Handscited by 0
  24. 2025Generative Diffusion Model Driven Massive Random Access in Massive MIMO Systemscited by 0
  25. 2025What Do You Need for Compositional Generalization in Diffusion Planning?cited by 0
  26. 2025Optimization-Free Diffusion Model -- A Perturbation Theory Approachcited by 0
  27. 2025Unrolling Nonconvex Graph Total Variation for Image Denoisingcited by 0
  28. 2025Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterizationcited by 0
  29. 2025Object-centric Denoising Diffusion Models for Physical Reasoningcited by 0
  30. 2025prNet: Data-Driven Phase Retrieval via Stochastic Refinementcited by 0
  31. 2025Fast 3D Diffusion for Scalable Granular Media Synthesiscited by 0
  32. 2025CSMapping: Scalable Crowdsourced Semantic Mapping and Topology Inference for Autonomous Drivingcited by 0
  33. 2026Estimation of instrument and noise parameters for inverse problem based on prior diffusion modelcited by 0
  34. 2026Active Diffusion Matching: Score-based Iterative Alignment of Cross-Modal Retinal Imagescited by 0
  35. 2026Particle Diffusion Matching: Random Walk Correspondence Search for the Alignment of Standard and Ultra-Widefield Fundus Imagescited by 0
  36. 2026KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problemscited by 0
  37. 2026Scene-aware Prediction of Diverse Human Movement Goalscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2022Diffusion Models: A Comprehensive Survey of Methods and Applications
  2. 2024A Comprehensive Survey on Diffusion Models and Their Applications
  3. 2023State of the Art on Diffusion Models for Visual Computing
  4. 2024Efficient Diffusion Models: A Comprehensive Survey from Principles to Practices
  5. 2023Understanding and contextualising diffusion models
  6. 2024Video Diffusion Models: A Survey
  7. 2022Diffusion Models in Vision: A Survey
  8. 2023Nested Diffusion Processes for Anytime Image Generation