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Richer Convolutional Features for Edge Detection

arXiv 1612.02103 ↗First posted 7 Dec 2016cs.CVcited by 141

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Abstract (arXiv)

In this paper, we propose an accurate edge detector using richer convolutional features (RCF). Since objects in nature images have various scales and aspect ratios, the automatically learned rich hierarchical representations by CNNs are very critical and effective to detect edges and object boundaries. And the convolutional features gradually become coarser with receptive fields increasing. Based on these observations, our proposed network architecture makes full use of multiscale and multi-level information to perform the image-to-image edge prediction by combining all of the useful convolutional features into a holistic framework. It is the first attempt to adopt such rich convolutional features in computer vision tasks. Using VGG16 network, we achieve sArt results on several available datasets. When evaluating on the well-known BSDS500 benchmark, we achieve ODS F-measure of .811 while retaining a fast speed (8 FPS). Besides, our fast version of RCF achieves ODS F-measure of .806 with 30 FPS.

Key facts. Cited by 141 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Dec 2016.

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Citing papers per year: 2021: 32; 2022: 23; 2023: 23; 2024: 25; 2025: 22; 2026: 16.

141 papers.

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  1. 2021Pixel Difference Networks for Efficient Edge Detectioncited by 167
  2. 2023Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modelingcited by 92
  3. 2021Applications of Deep Learning in Fundus Images: A Reviewcited by 59
  4. 2021Dense Extreme Inception Network for Edge Detectioncited by 37
  5. 2022EDTER: Edge Detection with Transformercited by 35
  6. 2021RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depthcited by 33
  7. 2024DiffusionEdge: Diffusion Probabilistic Model for Crisp Edge Detectioncited by 33
  8. 2021Does enhanced shape bias improve neural network robustness to common corruptions?cited by 32
  9. 2022Confusing Image Quality Assessment: Towards Better Augmented Reality Experiencecited by 32
  10. 2021Vision Transformers with Hierarchical Attentioncited by 31
  11. 2023Tiny and Efficient Model for the Edge Detection Generalizationcited by 28
  12. 2021PP-LCNet: A Lightweight CPU Convolutional Neural Networkcited by 27
38 more
  1. 2022Weakly-Supervised Salient Object Detection Using Point Supervisioncited by 25
  2. 2023The Treasure Beneath Multiple Annotations: An Uncertainty-aware Edge Detectorcited by 25
  3. 2021Generative Transformer for Accurate and Reliable Salient Object Detectioncited by 18
  4. 2024RankED: Addressing Imbalance and Uncertainty in Edge Detection Using Ranking-based Lossescited by 18
  5. 2024Lightweight Pixel Difference Networks for Efficient Visual Representation Learningcited by 17
  6. 2021Free-form tumor synthesis in computed tomography images via richer generative adversarial networkcited by 16
  7. 2021Improving Camouflaged Object Detection with the Uncertainty of Pseudo-edge Labelscited by 16
  8. 2021A Unified Efficient Pyramid Transformer for Semantic Segmentationcited by 14
  9. 2021HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastlinecited by 13
  10. 2022Weakly Supervised Video Salient Object Detection via Point Supervisioncited by 13
  11. 2021SLURP: Side Learning Uncertainty for Regression Problemscited by 12
  12. 2023Practical Edge Detection via Robust Collaborative Learningcited by 12
  13. 2024BEFUnet: A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentationcited by 11
  14. 2022Cross-SRN: Structure-Preserving Super-Resolution Network with Cross Convolutioncited by 10
  15. 2023Delving into Crispness: Guided Label Refinement for Crisp Edge Detectioncited by 10
  16. 2024EGGS: Edge Guided Gaussian Splatting for Radiance Fieldscited by 9
  17. 2025Rapid Salient Object Detection with Difference Convolutional Neural Networkscited by 9
  18. 2021Probabilistic Graph Attention Network with Conditional Kernels for Pixel-Wise Predictioncited by 8
  19. 2022Total Variation Optimization Layers for Computer Visioncited by 8
  20. 2021Learning Crisp Boundaries Using Deep Refinement Network and Adaptive Weighting Losscited by 7
  21. 2021Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Functioncited by 7
  22. 2022Scribble-based Boundary-aware Network for Weakly Supervised Salient Object Detection in Remote Sensing Imagescited by 7
  23. 2024SAUGE: Taming SAM for Uncertainty-Aligned Multi-Granularity Edge Detectioncited by 7
  24. 2021Learning Deep Morphological Networks with Neural Architecture Searchcited by 6
  25. 2022Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Featurecited by 6
  26. 2023Revisiting Computer-Aided Tuberculosis Diagnosiscited by 6
  27. 2023MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioningcited by 6
  28. 2024RFL-CDNet: Towards Accurate Change Detection via Richer Feature Learningcited by 6
  29. 2024LogicAL: Towards logical anomaly synthesis for unsupervised anomaly localizationcited by 6
  30. 2024EdgeNAT: Transformer for Efficient Edge Detectioncited by 6
  31. 2024Staircase Cascaded Fusion of Lightweight Local Pattern Recognition and Long-Range Dependencies for Structural Crack Segmentationcited by 6
  32. 2024SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy datacited by 6
  33. 20223SD: Self-Supervised Saliency Detection With No Labelscited by 5
  34. 2022One-Stage Deep Edge Detection Based on Dense-Scale Feature Fusion and Pixel-Level Imbalance Learningcited by 5
  35. 2023Mobile-Seed: Joint Semantic Segmentation and Boundary Detection for Mobile Robotscited by 5
  36. 2024Generative Edge Detection with Stable Diffusioncited by 5
  37. 2025Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagerycited by 5
  38. 2021Graph Jigsaw Learning for Cartoon Face Recognitioncited by 4

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