Codes-for-Lane-Detection and LaneATT

Codes-for-Lane-Detection

Established

LaneATT

Established

Maintenance 0/25

Adoption 10/25

Maturity 16/25

Community 25/25

Maintenance 0/25

Adoption 10/25

Maturity 16/25

Community 25/25

Stars: 1,066

Forks: 335

Downloads: —

Commits (30d): 0

Language: Lua

License: MIT

Stars: 693

Forks: 178

Downloads: —

Commits (30d): 0

Language: Python

License: MIT

Stale 6m No Package No Dependents

About Codes-for-Lane-Detection

cardwing/Codes-for-Lane-Detection

Learning Lightweight Lane Detection CNNs by Self Attention Distillation (ICCV 2019)

This project offers robust and efficient systems for detecting lane lines in real-time traffic camera footage. It takes video frames or images as input and outputs precise lane markings, even in challenging conditions like night driving or bad weather. Autonomous vehicle developers and researchers can use this to integrate advanced lane detection capabilities into their systems.

autonomous-driving vehicle-perception traffic-scene-understanding computer-vision robotics

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

Related comparisons

Codes-for-Lane-Detection and Ultra-Fast-Lane-Detection-v2 Codes-for-Lane-Detection and Eigenlanes

Scores updated daily from GitHub, PyPI, and npm data. How scores work