mlsanityData to 7 Oct 2026

What are the Receptive, Effective Receptive, and Projective Fields of Neurons in Convolutional Neural Networks?

arXiv 1705.07049 ↗First posted 19 May 2017cs.CVcited by 16

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Abstract (arXiv)

In this work, we explain in detail how receptive fields, effective receptive fields, and projective fields of neurons in different layers, convolution or pooling, of a Convolutional Neural Network (CNN) are calculated. While our focus here is on CNNs, the same operations, but in the reverse order, can be used to calculate these quantities for deconvolutional neural networks. These are important concepts, not only for better understanding and analyzing convolutional and deconvolutional networks, but also for optimizing their performance in real-world applications.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 May 2017.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 3; 2024: 2; 2025: 3.

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  1. 2021Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Mergingcited by 104
  2. 2023PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defensescited by 10
  3. 2021Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstructioncited by 6
  4. 2021Deep Learning for Robust Motion Segmentation with Non-Static Camerascited by 5
  5. 2024Feature Accentuation: Revealing 'What' Features Respond to in Natural Imagescited by 5
  6. 2022Pruning for Feature-Preserving Circuits in CNNscited by 4
  7. 2022Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performancecited by 4
  8. 2023High-Performance Transformers for Table Structure Recognition Need Early Convolutionscited by 4
  9. 2021Self-Supervised Learning of Perceptually Optimized Block Motion Estimates for Video Compressioncited by 2
  10. 2025Bigger Isn't Always Better: Towards a General Prior for Medical Image Reconstructioncited by 2
  11. 2021Real-time Human Detection Model for Edge Devicescited by 1
  12. 2023Balanced Mixture of SuperNets for Learning the CNN Pooling Architecturecited by 1
4 more
  1. 2022Fast-ParC: Capturing Position Aware Global Feature for ConvNets and ViTscited by 0
  2. 2024Robust Curve Detection in Volumetric Medical Imaging via Attraction Fieldcited by 0
  3. 2025Generative Fields: Uncovering Hierarchical Feature Control for StyleGAN via Inverted Receptive Fieldscited by 0
  4. 2025Learning to Borrow Features for Improved Detection of Small Objects in Single-Shot Detectorscited by 0