PINet Lightweight Lane Detection

Project Overview

PINet (Point Instance Network) is an end-to-end framework developed for accurate and lightweight lane detection. The network detects key points and clusters them to represent each traffic lane instance, providing a structured approach to lane recognition that is both computationally efficient and highly accurate.

Objectives

• Instance Segmentation: Use key points to differentiate lane instances.
• Efficiency and Lightweight: Minimize computational requirements without sacrificing accuracy.
• Real-Time Performance: Ensure quick lane detection suitable for autonomous driving applications.

Highlights

This project achieved:

• Enhanced accuracy in lane detection through a key-point clustering method, facilitating better traffic lane visualization.
• Real-time processing capability, making it adaptable for real-world applications.
• Low computational footprint, ideal for embedded systems in autonomous vehicles.

Visual Gallery

PINet Lane Detection

A practical example of lane detection using the PINet framework, highlighting accurate clustering of key points.

Additional Resources

For detailed code and documentation on PINet, visit the GitHub repository