mlsanityData to 14 Oct 2026

WavEnhancer: Unifying Wavelet and Transformer for Image Enhancement

arXiv 2212.08327 ↗First posted 16 Dec 2022cs.CV eess.IVcited by 11

Not on the map. Why?

Abstract (arXiv)

Image enhancement is a technique that frequently utilized in digital image processing. In recent years, the popularity of learning-based techniques for enhancing the aesthetic performance of photographs has increased. However, the majority of current works do not optimize an image from different frequency domains and typically focus on either pixel-level or global-level enhancements. In this paper, we propose a transformer-based model in the wavelet domain to refine different frequency bands of an image. Our method focuses both on local details and high-level features for enhancement, which can generate superior results. On the basis of comprehensive benchmark evaluations, our method outperforms the state-of-the-art methods.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 19 of its 34 references that are in the map. First posted on arXiv 16 Dec 2022.

Builds on

19 of 34 references.

References · 19

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  4. 2016Layer Normalizationcited by 5,669
  5. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,694
  6. 2021Restormer: Efficient Transformer for High-Resolution Image Restorationcited by 1,627
  7. 2017Deep Bilateral Learning for Real-Time Image Enhancementcited by 200
  8. 2019Photorealistic Style Transfer via Wavelet Transformscited by 166
  9. 2020Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-timecited by 163
  10. 2020DeepLPF: Deep Local Parametric Filters for Image Enhancementcited by 107
  11. 2019Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GANcited by 103
  12. 2018Single Image Reflection Separation with Perceptual Lossescited by 98
7 more
  1. 2022Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learningcited by 78
  2. 2020Conditional Sequential Modulation for Efficient Global Image Retouchingcited by 71
  3. 2019Multi-level Wavelet Convolutional Neural Networkscited by 59
  4. 2020Wavelet-Based Dual-Branch Network for Image Demoireingcited by 55
  5. 2022SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancementcited by 50
  6. 2019Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layerscited by 39
  7. 2020Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domaincited by 24

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 8.

11 papers.

  1. 2024DOPRA: Decoding Over-accumulation Penalization and Re-allocation in Specific Weighting Layercited by 27
  2. 2024Dual-Hybrid Attention Network for Specular Highlight Removalcited by 18
  3. 2024SMAFormer: Synergistic Multi-Attention Transformer for Medical Image Segmentationcited by 14
  4. 2024Test-Time Intensity Consistency Adaptation for Shadow Detectioncited by 11
  5. 2023DocDeshadower: Frequency-Aware Transformer for Document Shadow Removalcited by 9
  6. 2023UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformercited by 9
  7. 2024Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Modelcited by 6
  8. 2023ShaDocFormer: A Shadow-Attentive Threshold Detector With Cascaded Fusion Refiner for Document Shadow Removalcited by 2
  9. 2024UIE-UnFold: Deep Unfolding Network with Color Priors and Vision Transformer for Underwater Image Enhancementcited by 2
  10. 2024Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentationcited by 0
  11. 2024Adaptive Query Prompting for Multi-Domain Landmark Detectioncited by 0