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Gated Context Aggregation Network for Image Dehazing and Deraining

arXiv 1811.08747 ↗First posted 21 Nov 2018cs.CVcited by 89

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Abstract (arXiv)

Image dehazing aims to recover the uncorrupted content from a hazy image. Instead of leveraging traditional low-level or handcrafted image priors as the restoration constraints, e.g., dark channels and increased contrast, we propose an end-to-end gated context aggregation network to directly restore the final haze-free image. In this network, we adopt the latest smoothed dilation technique to help remove the gridding artifacts caused by the widely-used dilated convolution with negligible extra parameters, and leverage a gated sub-network to fuse the features from different levels. Extensive experiments demonstrate that our method can surpass previous state-of-the-art methods by a large margin both quantitatively and qualitatively. In addition, to demonstrate the generality of the proposed method, we further apply it to the image deraining task, which also achieves the state-of-the-art performance. Code has been made available at https://github.com/cddlyf/GCANet.

Key facts. Cited by 89 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Nov 2018.

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Citing papers per year: 2021: 16; 2022: 18; 2023: 23; 2024: 15; 2025: 13; 2026: 4.

89 papers.

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  1. 2022MAXIM: Multi-Axis MLP for Image Processingcited by 301
  2. 2022Vision Transformers for Single Image Dehazingcited by 255
  3. 2021Contrastive Learning for Compact Single Image Dehazingcited by 219
  4. 2024InstructIR: High-Quality Image Restoration Following Human Instructionscited by 139
  5. 2023Controlling Vision-Language Models for Multi-Task Image Restorationcited by 108
  6. 2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
  7. 2023Curricular Contrastive Regularization for Physics-aware Single Image Dehazingcited by 83
  8. 2023GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditionscited by 62
  9. 2021Deep Model Intellectual Property Protection via Deep Watermarkingcited by 47
  10. 2024U-shaped Vision Mamba for Single Image Dehazingcited by 40
  11. 2022UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learningcited by 35
  12. 2023Towards Unified Deep Image Deraining: A Survey and A New Benchmarkcited by 34
38 more
  1. 2023Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Priorcited by 22
  2. 2022Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learningcited by 21
  3. 2021A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learningcited by 19
  4. 2023MixDehazeNet : Mix Structure Block For Image Dehazing Networkcited by 18
  5. 2021Towards Domain Invariant Single Image Dehazingcited by 17
  6. 2023Frequency Compensated Diffusion Model for Real-scene Dehazingcited by 17
  7. 2021A Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble Learningcited by 16
  8. 2023SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazingcited by 15
  9. 2023HQ-50K: A Large-scale, High-quality Dataset for Image Restorationcited by 15
  10. 2021Visible Watermark Removal via Self-calibrated Localization and Background Refinementcited by 14
  11. 2024RSDehamba: Lightweight Vision Mamba for Remote Sensing Satellite Image Dehazingcited by 14
  12. 2022Single UHD Image Dehazing via Interpretable Pyramid Networkcited by 13
  13. 2023Let Segment Anything Help Image Dehazecited by 13
  14. 2022Rethinking Performance Gains in Image Dehazing Networkscited by 12
  15. 2025Exploiting Diffusion Prior for Real-World Image Dehazing with Unpaired Trainingcited by 12
  16. 2025NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Resultscited by 12
  17. 2021U2-Former: A Nested U-shaped Transformer for Image Restorationcited by 10
  18. 2022A Multi-purpose Realistic Haze Benchmark with Quantifiable Haze Levels and Ground Truthcited by 9
  19. 2023A Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformercited by 9
  20. 2023Breaking Through the Haze: An Advanced Non-Homogeneous Dehazing Method based on Fast Fourier Convolution and ConvNeXtcited by 8
  21. 2021Debiased Subjective Assessment of Real-World Image Enhancementcited by 7
  22. 2021Computational Imaging and Artificial Intelligence: The Next Revolution of Mobile Visioncited by 7
  23. 2022FogAdapt: Self-Supervised Domain Adaptation for Semantic Segmentation of Foggy Imagescited by 7
  24. 2023Video Waterdrop Removal via Spatio-Temporal Fusion in Driving Scenescited by 7
  25. 2023Illumination Controllable Dehazing Network based on Unsupervised Retinex Embeddingcited by 7
  26. 2021Non-Homogeneous Haze Removal via Artificial Scene Prior and Bidimensional Graph Reasoningcited by 6
  27. 2024Real-Time Multi-Scene Visibility Enhancement for Promoting Navigational Safety of Vessels Under Complex Weather Conditionscited by 5
  28. 2025UniSER: A Foundation Model for Unified Soft Effects Removalcited by 5
  29. 2022Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstructioncited by 4
  30. 2022Deep Idempotent Network for Efficient Single Image Blind Deblurringcited by 4
  31. 2022Semi-UFormer: Semi-supervised Uncertainty-aware Transformer for Image Dehazingcited by 4
  32. 2022Relationship Quantification of Image Degradationscited by 4
  33. 2023Reliable Image Dehazing by NeRFcited by 4
  34. 2024WaveletFormerNet: A Transformer-based Wavelet Network for Real-world Non-homogeneous and Dense Fog Removalcited by 4
  35. 2025Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removalcited by 4
  36. 2021ISP-Agnostic Image Reconstruction for Under-Display Camerascited by 3
  37. 2022Multi-Curve Translator for High-Resolution Photorealistic Image Translationcited by 3
  38. 2022QSAM-Net: Rain streak removal by quaternion neural network with self-attention modulecited by 3

50 most cited of 89 All 89 (JSON)