mlsanityData to 7 Oct 2026

Gabor Convolutional Networks

arXiv 1705.01450 ↗First posted 3 May 2017cs.CVcited by 55

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Abstract (arXiv)

Steerable properties dominate the design of traditional filters, e.g., Gabor filters, and endow features the capability of dealing with spatial transformations. However, such excellent properties have not been well explored in the popular deep convolutional neural networks (DCNNs). In this paper, we propose a new deep model, termed Gabor Convolutional Networks (GCNs or Gabor CNNs), which incorporates Gabor filters into DCNNs to enhance the resistance of deep learned features to the orientation and scale changes. By only manipulating the basic element of DCNNs based on Gabor filters, i.e., the convolution operator, GCNs can be easily implemented and are compatible with any popular deep learning architecture. Experimental results demonstrate the super capability of our algorithm in recognizing objects, where the scale and rotation changes occur frequently. The proposed GCNs have much fewer learnable network parameters, and thus is easier to train with an end-to-end pipeline.

Key facts. Cited by 55 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 May 2017.

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Citing papers per year: 2021: 14; 2022: 12; 2023: 6; 2024: 11; 2025: 7; 2026: 5.

55 papers.

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  1. 2021Pixel Difference Networks for Efficient Edge Detectioncited by 167
  2. 2021Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Seriescited by 29
  3. 2021Resolution learning in deep convolutional networks using scale-space theorycited by 26
  4. 2024Lightweight Pixel Difference Networks for Efficient Visual Representation Learningcited by 17
  5. 2023Learning Gabor Texture Features for Fine-Grained Recognitioncited by 16
  6. 2023Mechanism of feature learning in convolutional neural networkscited by 15
  7. 2022Local Intensity Order Transformation for Robust Curvilinear Object Segmentationcited by 12
  8. 2021Spectral Leakage and Rethinking the Kernel Size in CNNscited by 11
  9. 2024Wavelet-Based Image Tokenizer for Vision Transformerscited by 10
  10. 2025From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learningcited by 10
  11. 20253DGabSplat: 3D Gabor Splatting for Frequency-adaptive Radiance Field Renderingcited by 10
  12. 2022Orientation and Context Entangled Network for Retinal Vessel Segmentationcited by 8
38 more
  1. 2023Riesz networks: scale invariant neural networks in a single forward passcited by 8
  2. 2022Context-Aware Scene Prediction Network (CASPNet)cited by 7
  3. 2021PCNet: A Structure Similarity Enhancement Method for Multispectral and Multimodal Image Registrationcited by 6
  4. 2021Uncertainty-Guided Lung Nodule Segmentation with Feature-Aware Attentioncited by 6
  5. 2021Frequency learning for structured CNN filters with Gaussian fractional derivativescited by 6
  6. 2021Interpretable Deep Feature Propagation for Early Action Recognitioncited by 5
  7. 20223D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficientcited by 5
  8. 2021Wallpaper Texture Generation and Style Transfer Based on Multi-label Semanticscited by 4
  9. 2023Lung Nodule Segmentation and Uncertain Region Prediction with an Uncertainty-Aware Attention Mechanismcited by 3
  10. 2024FViT: A Focal Vision Transformer with Gabor Filtercited by 3
  11. 2024Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variationscited by 3
  12. 2022The Brain-Inspired Decoder for Natural Visual Image Reconstructioncited by 2
  13. 2022Frequency Dropout: Feature-Level Regularization via Randomized Filteringcited by 2
  14. 2022On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networkscited by 2
  15. 2023Representation Learning in a Decomposed Encoder Design for Bio-inspired Hebbian Learningcited by 2
  16. 2024Deep Continuous Networkscited by 2
  17. 2024PDE-CNNs: Axiomatic Derivations and Applicationscited by 2
  18. 2024MomentsNeRF: Leveraging Orthogonal Moments for Few-Shot Neural Renderingcited by 2
  19. 2025Bridging Classical and Modern Computer Vision: PerceptiveNet for Tree Crown Semantic Segmentationcited by 2
  20. 2021Touchless Palmprint Recognition based on 3D Gabor Template and Block Feature Refinementcited by 1
  21. 2022Gabor is Enough: Interpretable Deep Denoising with a Gabor Synthesis Dictionary Priorcited by 1
  22. 2022GraSens: A Gabor Residual Anti-aliasing Sensing Framework for Action Recognition using WiFicited by 1
  23. 2022What do CNNs Learn in the First Layer and Why? A Linear Systems Perspectivecited by 1
  24. 2024EMWaveNet: Physically Explainable Neural Network Based on Electromagnetic Propagation for SAR Target Recognitioncited by 1
  25. 2025Uncertainty-Aware Decomposed Hybrid Networkscited by 1
  26. 2021Orientation Convolutional Networks for Image Recognitioncited by 0
  27. 2021Time-Frequency Localization Using Deep Convolutional Maxout Neural Network in Persian Speech Recognitioncited by 0
  28. 2021A Cascaded Zoom-In Network for Patterned Fabric Defect Detectioncited by 0
  29. 2021Gabor filter incorporated CNN for compressioncited by 0
  30. 2022OneDConv: Generalized Convolution For Transform-Invariant Representationcited by 0
  31. 2022Rega-Net:Retina Gabor Attention for Deep Convolutional Neural Networkscited by 0
  32. 2023ExplainFix: Explainable Spatially Fixed Deep Networkscited by 0
  33. 2024Analytic Convolutional Layer: A Step to Analytic Neural Networkcited by 0
  34. 2024Multi-scale gridded Gabor attention for cirrus segmentationcited by 0
  35. 2024Parametric PerceptNet: A bio-inspired deep-net trained for Image Quality Assessmentcited by 0
  36. 2025Rethinking Rotation-Invariant Recognition of Fine-grained Shapes from the Perspective of Contour Pointscited by 0
  37. 2025Beyond sparse denoising in frames: minimax estimation with a scattering transformcited by 0
  38. 2025Accelerated Rotation-Invariant Convolution for UAV Image Segmentationcited by 0

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