awesome-edge-detection-papers
github.com/markmohr/awesome-edge-detection-papers ↗:books: A collection of edge/contour/boundary detection papers and toolbox.
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me 1.1 general edge detection resources from awesome-edge-detection-papers"
Installation instructions →What's inside
1. Deep-learning based approaches
- AMH-Net1.1 General edge detection
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
- BDCN1.1 General edge detection
Bi-Directional Cascade Network for Perceptual Edge Detection
- CASENet1.3 Semantic edge detection (Category-Aware)
CASENet: Deep Category-Aware Semantic Edge Detection
- CED1.1 General edge detection
Deep Crisp Boundaries
- CEDN1.2 Object contour detection
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
- COB1.1 General edge detection
Convolutional Oriented Boundaries
2. Traditional approaches
- Canny
A Computational Approach to Edge Detection
- Edge Boxes
Edge Boxes: Locating Object Proposals from Edges
- FDoG
Coherent Line Drawing
- gPb-owt-ucm
Contour Detection and Hierarchical Image Segmentation
- OEF
Oriented Edge Forests for Boundary Detection
- PMI
Crisp Boundary Detection Using Pointwise Mutual Information
3. Useful Links
Showing a sample of 36 resources. View the full list on GitHub →