mlsanityData to 14 Oct 2026

Fast Guided Filter

arXiv 1505.00996 ↗First posted 5 May 2015cs.CVcited by 12

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Abstract (arXiv)

The guided filter is a technique for edge-aware image filtering. Because of its nice visual quality, fast speed, and ease of implementation, the guided filter has witnessed various applications in real products, such as image editing apps in phones and stereo reconstruction, and has been included in official MATLAB and OpenCV. In this note, we remind that the guided filter can be simply sped up from O(N) time to O(N/s^2) time for a subsampling ratio s. In a variety of applications, this leads to a speedup of >10x with almost no visible degradation. We hope this acceleration will improve performance of current applications and further popularize this filter. Code is released.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 May 2015.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 3; 2025: 3; 2026: 1.

12 papers.

  1. 2024A Refreshed Similarity-based Upsampler for Direct High-Ratio Feature Upsamplingcited by 7
  2. 2025NAF: Zero-Shot Feature Upsampling via Neighborhood Attention Filteringcited by 6
  3. 2022Water Simulation and Rendering from a Still Photographcited by 5
  4. 2023YOLO-Angio: An Algorithm for Coronary Anatomy Segmentationcited by 4
  5. 2025FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolutioncited by 3
  6. 2021Deterministic Guided LiDAR Depth Map Completioncited by 2
  7. 2024MvKSR: Multi-view Knowledge-guided Scene Recovery for Hazy and Rainy Degradationcited by 2
  8. 2021Image Enhancement via Bilateral Learningcited by 1
  9. 2023A Machine Vision Method for Correction of Eccentric Error: Based on Adaptive Enhancement Algorithmcited by 0
  10. 2024Fast Local Neural Regression for Low-Cost, Path Traced Lambertian Global Illuminationcited by 0
  11. 2025Adaptive Guided Upsampling for Low-light Image Enhancementcited by 0
  12. 2026ViT-Up: Faithful Feature Upsampling for Vision Transformerscited by 0