mlsanityData to 7 Oct 2026

Zero-Shot Video Restoration and Enhancement with Assistance of Video Diffusion Models

arXiv 2601.21922 ↗First posted 29 Jan 2026cs.CVcited by 0

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

Abstract (arXiv)

Although diffusion-based zero-shot image restoration and enhancement methods have achieved great success, applying them to video restoration or enhancement will lead to severe temporal flickering. In this paper, we propose the first framework that utilizes the rapidly-developed video diffusion model to assist the image-based method in maintaining more temporal consistency for zero-shot video restoration and enhancement. We propose homologous latents fusion, heterogenous latents fusion, and a COT-based fusion ratio strategy to utilize both homologous and heterogenous text-to-video diffusion models to complement the image method. Moreover, we propose temporal-strengthening post-processing to utilize the image-to-video diffusion model to further improve temporal consistency. Our method is training-free and can be applied to any diffusion-based image restoration and enhancement methods. Experimental results demonstrate the superiority of the proposed method.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Inverse problems and image restoration, one of 14 directions in Diffusion models. Builds on 51 of its 61 references that are in the map. First posted on arXiv 29 Jan 2026.

Builds on

51 of 61 references.

Closest ancestors · 16

Same direction, newest first

  1. 2025DiT4SR: Taming Diffusion Transformer for Real-World Image Super-Resolution30 Mar
  2. 2025SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restoration2 Jan
  3. 2024VISION-XL: High Definition Video Inverse Problem Solver using Latent Image Diffusion Models29 Nov
  4. 2024TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-Resolution27 Nov
  5. 2024Solving Video Inverse Problems Using Image Diffusion Models4 Sep
  6. 2024Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Model2 Jul
  7. 2024DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration Models1 Jul
  8. 2023Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution11 Dec
  9. 2023Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion1 Dec
  10. 2023Prompt-tuning latent diffusion models for inverse problems2 Oct
  11. 2023Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models2 Jul
  12. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolution11 May
4 more
  1. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancement3 Apr
  2. 2022Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model1 Dec
  3. 2022Diffusion Posterior Sampling for General Noisy Inverse Problems29 Sep
  4. 2022Denoising Diffusion Restoration Models27 Jan

Other references · 35

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2020Denoising Diffusion Implicit Modelscited by 9,655
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  5. 2023Let's Verify Step by Stepcited by 3,598
  6. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  7. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,526
  8. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  9. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,198
  10. 2024Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameterscited by 1,928
  11. 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,597
  12. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
23 more
  1. 2022Exploring CLIP for Assessing the Look and Feel of Imagescited by 974
  2. 2022Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generationcited by 958
  3. 2023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generatorscited by 666
  4. 2023ModelScope Text-to-Video Technical Reportcited by 651
  5. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  6. 2023FateZero: Fusing Attentions for Zero-shot Text-based Video Editingcited by 462
  7. 2021BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignmentcited by 340
  8. 2022Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectivescited by 314
  9. 2023Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translationcited by 253
  10. 2018Learning Blind Video Temporal Consistencycited by 247
  11. 2018TDAN: Temporally Deformable Alignment Network for Video Super-Resolutioncited by 225
  12. 2022VRT: A Video Restoration Transformercited by 219
  13. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 133
  14. 2025Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Stepcited by 130
  15. 2023VidToMe: Video Token Merging for Zero-Shot Video Editingcited by 111
  16. 2023Let's reward step by step: Step-Level reward model as the Navigators for Reasoningcited by 96
  17. 2021Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancementcited by 60
  18. 2023Enhancing Video Super-Resolution via Implicit Resampling-based Alignmentcited by 35
  19. 2024Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attentioncited by 29
  20. 2024FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurringcited by 28
  21. 2023FastLLVE: Real-Time Low-Light Video Enhancement with Intensity-Aware Lookup Tablecited by 15
  22. 2024Unrolled Decomposed Unpaired Learning for Controllable Low-Light Video Enhancementcited by 7
  23. 2023Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Modelscited by 4

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  3. 2025Improving Temporal Consistency and Fidelity at Inference-time in Perceptual Video Restoration by Zero-shot Image-based Diffusion Models
  4. 2025Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual
  5. 2023Unlimited-Size Diffusion Restoration
  6. 2023Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Models
  7. 2025TDM: Temporally-Consistent Diffusion Model for All-in-One Real-World Video Restoration
  8. 2026ZeroIDIR: Zero-Reference Illumination Degradation Image Restoration with Perturbed Consistency Diffusion Models