mlsanityData to 7 Oct 2026

ViDeNN: Deep Blind Video Denoising

arXiv 1904.10898 ↗First posted 24 Apr 2019cs.CVcited by 40

Not on the map. Why?

Abstract (arXiv)

We propose ViDeNN: a CNN for Video Denoising without prior knowledge on the noise distribution (blind denoising). The CNN architecture uses a combination of spatial and temporal filtering, learning to spatially denoise the frames first and at the same time how to combine their temporal information, handling objects motion, brightness changes, low-light conditions and temporal inconsistencies. We demonstrate the importance of the data used for CNNs training, creating for this purpose a specific dataset for low-light conditions. We test ViDeNN on common benchmarks and on self-collected data, achieving good results comparable with the state-of-the-art.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Apr 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 12; 2023: 5; 2024: 9; 2025: 4; 2026: 2.

40 papers.

Sort:

  1. 2022Dancing under the stars: video denoising in starlightcited by 47
  2. 2022RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolutioncited by 44
  3. 2021Patch Craft: Video Denoising by Deep Modeling and Patch Matchingcited by 38
  4. 2022Bringing Old Films Back to Lifecited by 31
  5. 2023Blind Video Deflickering by Neural Filtering with a Flawed Atlascited by 27
  6. 2022Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Onescited by 24
  7. 2025AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Resultscited by 14
  8. 2021Contextual colorization and denoising for low-light ultra high resolution sequencescited by 10
  9. 2021Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and Video Denoisingcited by 9
  10. 2022Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super Resolutioncited by 9
  11. 2023Recurrent Self-Supervised Video Denoising with Denser Receptive Fieldcited by 8
  12. 2023A Comparison of Image Denoising Methodscited by 7
28 more
  1. 2022Learning Task-Oriented Flows to Mutually Guide Feature Alignment in Synthesized and Real Video Denoisingcited by 5
  2. 2026Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoisingcited by 5
  3. 2021Multi-Stage Raw Video Denoising with Adversarial Loss and Gradient Maskcited by 4
  4. 2021Frequency Domain Loss Function for Deep Exposure Correction of Dark Imagescited by 4
  5. 2022RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compressioncited by 4
  6. 2022Self-supervision versus synthetic datasets: which is the lesser evil in the context of video denoising?cited by 3
  7. 2022Coarse-to-Fine Video Denoising with Dual-Stage Spatial-Channel Transformercited by 3
  8. 2023Unsupervised Coordinate-Based Video Denoisingcited by 3
  9. 2023BONES: Near-Optimal Neural-Enhanced Video Streamingcited by 3
  10. 2024Quanta Video Restorationcited by 3
  11. 2021A Lightweight Structure Aimed to Utilize Spatial Correlation for Sparse-View CT Reconstructioncited by 2
  12. 2021Fast and Accurate: Video Enhancement using Sparse Depthcited by 2
  13. 2024VJT: A Video Transformer on Joint Tasks of Deblurring, Low-light Enhancement and Denoisingcited by 2
  14. 2024Unsupervised Microscopy Video Denoisingcited by 2
  15. 2024Lightweight Video Denoising Using a Classic Bayesian Backbonecited by 2
  16. 2025Joint Flow And Feature Refinement Using Attention For Video Restorationcited by 2
  17. 2022Stabilize, Decompose, and Denoise: Self-Supervised Fluoroscopy Denoisingcited by 1
  18. 2024Color Image Denoising Using The Green Channel Priorcited by 1
  19. 2026AbsoluteDegradation: A Physics-Inspired Synthetic Film-Degradation Pipeline and Archival Film Restoration Benchmarkcited by 1
  20. 2021Real-Time Limited-View CT Inpainting and Reconstruction with Dual Domain Based on Spatial Informationcited by 0
  21. 2022Towards Real-World Video Denosing: A Practical Video Denosing Dataset and Networkcited by 0
  22. 2022Gated Recurrent Unit for Video Denoisingcited by 0
  23. 2024Technique Report of CVPR 2024 PBDL Challengescited by 0
  24. 2024Learning Instance-Specific Parameters of Black-Box Models Using Differentiable Surrogatescited by 0
  25. 2024Cascading Refinement Video Denoising with Uncertainty Adaptivitycited by 0
  26. 2024A Practical Gated Recurrent Transformer Network Incorporating Multiple Fusions for Video Denoisingcited by 0
  27. 2025Efficient Image Denoising Using Global and Local Circulant Representationcited by 0
  28. 2025Image Denoising Using Global and Local Circulant Representationcited by 0