LaneATT and Ultra-Fast-Lane-Detection-v2

LaneATT
51
Established
Ultra-Fast-Lane-Detection-v2
50
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Stars: 693
Forks: 178
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 792
Forks: 143
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About LaneATT

lucastabelini/LaneATT

Code for the paper entitled "Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection" (CVPR 2021)

This project provides an advanced system for real-time lane detection in vehicle camera feeds. It takes raw video or image data from a vehicle's perspective and outputs precise information about lane markings. This is useful for engineers and researchers developing autonomous driving systems or advanced driver-assistance features.

autonomous-driving vehicle-perception lane-keeping ADAS computer-vision

About Ultra-Fast-Lane-Detection-v2

cfzd/Ultra-Fast-Lane-Detection-v2

Ultra Fast Deep Lane Detection With Hybrid Anchor Driven Ordinal Classification (TPAMI 2022)

This project helps self-driving car engineers and researchers detect lane lines in real-time video feeds. It takes video footage of roads as input and accurately identifies and outlines lane markings, even under challenging conditions. The output is a visual representation of detected lanes, crucial for autonomous navigation systems.

autonomous-driving lane-keeping computer-vision driver-assistance robotics-navigation

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