mlsanityData to 14 Oct 2026

Efficient Burst Super-Resolution with One-step Diffusion

arXiv 2507.13607 ↗First posted 18 Jul 2025cs.CVcited by 2

On the map: Diffusion models → Inverse problems and image restoration

Abstract (arXiv)

While burst Low-Resolution (LR) images are useful for improving their Super Resolution (SR) image compared to a single LR image, prior burst SR methods are trained in a deterministic manner, which produces a blurry SR image. Since such blurry images are perceptually degraded, we aim to reconstruct sharp and high-fidelity SR images by a diffusion model. Our method improves the efficiency of the diffusion model with a stochastic sampler with a high-order ODE as well as one-step diffusion using knowledge distillation. Our experimental results demonstrate that our method can reduce the runtime to 1.6 % of its baseline while maintaining the SR quality measured based on image distortion and perceptual quality.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Inverse problems and image restoration, one of 14 directions in Diffusion models. Builds on 41 of its 51 references that are in the map. First posted on arXiv 18 Jul 2025.

Builds on

41 of 51 references.

Closest ancestors · 12

Same direction, newest first

  1. 2024Burst Super-Resolution with Diffusion Models for Improving Perceptual Quality28 Mar
  2. 2024Efficient Diffusion Model for Image Restoration by Residual Shifting12 Mar
  3. 2023SinSR: Diffusion-Based Image Super-Resolution in a Single Step23 Nov
  4. 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting23 Jul
  5. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolution11 May
  6. 2023GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration30 Jan
  7. 2022Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems20 Nov
  8. 2022Parallel Diffusion Models of Operator and Image for Blind Inverse Problems19 Nov
  9. 2022Diffusion Posterior Sampling for General Noisy Inverse Problems29 Sep
  10. 2022Improving Diffusion Models for Inverse Problems using Manifold Constraints2 Jun
  11. 2022Denoising Diffusion Restoration Models27 Jan
  12. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction9 Dec

Other references · 29

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  4. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  5. 2020Denoising Diffusion Implicit Modelscited by 9,781
  6. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  7. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  8. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 3,045
  9. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,937
  10. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
  11. 2023Consistency Modelscited by 1,822
  12. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
17 more
  1. 2017Deformable Convolutional Networkscited by 1,488
  2. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,224
  3. 2021Video Swin Transformercited by 1,091
  4. 2023Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusioncited by 459
  5. 2018Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transformcited by 371
  6. 2022Perception Prioritized Training of Diffusion Modelscited by 303
  7. 2018Deep Back-Projection Networks For Super-Resolutioncited by 225
  8. 2019Recurrent Back-Projection Network for Video Super-Resolutioncited by 148
  9. 2021Deep Burst Super-Resolutioncited by 83
  10. 2021Burst Image Restoration and Enhancementcited by 64
  11. 2020Space-Time-Aware Multi-Resolution Video Enhancementcited by 49
  12. 2022BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignmentcited by 32
  13. 2023Burstormer: Burst Image Restoration and Enhancement Transformercited by 32
  14. 2021NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Resultscited by 22
  15. 2019Deep Back-Projection Networks for Single Image Super-resolutioncited by 16
  16. 2022A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shiftcited by 10
  17. 2020AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Resultscited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusioncited by 7
  2. 2026It Takes Two: A Duet of Periodicity and Directionality for Burst Flicker Removalcited by 4

Similar, not cited

Close in wording, no citation either way

  1. 2024Degradation-Guided One-Step Image Super-Resolution with Diffusion Priors
  2. 2023ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution
  3. 2025One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation
  4. 2024One Step Diffusion-based Super-Resolution with Time-Aware Distillation
  5. 2026BurstGP: Enhancing Raw Burst Image Super Resolution with Generative Priors
  6. 2024Arbitrary-steps Image Super-resolution via Diffusion Inversion
  7. 2024TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-Resolution
  8. 2026Uncertainty-Guided Latent Diffusion Models for Faithful Super Resolution