Lane Detection
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Lane Detection is a computer vision task that involves identifying the boundaries of driving lanes in a video or image of a road scene. The goal is to accurately locate and track the lane markings in real-time, even in challenging conditions such as poor lighting, glare, or complex road layouts.
Lane detection is an important component of advanced driver assistance systems (ADAS) and autonomous vehicles, as it provides information about the road layout and the position of the vehicle within the lane, which is crucial for navigation and safety. The algorithms typically use a combination of computer vision techniques, such as edge detection, color filtering, and Hough transforms, to identify and track the lane markings in a road scene.
<span style="color:grey; opacity: 0.6">( Image credit: End-to-end Lane Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/GuangyanZhang/SCNN-Deeplabv3-bisenet-icnet
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
https://github.com/Harlequln/C1M18X-Behavioural_Cloning
https://github.com/HarshaVardhanVanama/Autopilot-Steering-Control
https://github.com/HarshaVardhanVanama/Autopilot-Steering-Wheel-Simulation
https://github.com/Hp990/Self-driving-car
https://github.com/Huangdebo/YOLOv4-MultiTask
https://github.com/HussainGhazaly/PINet-master
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
https://github.com/IrohXu/lanenet-lane-detection-pytorch
Towards End-to-End Lane Detection: an Instance Segmentation Approach
https://github.com/IvanVassi/LaneNet
Towards End-to-End Lane Detection: an Instance Segmentation Approach
https://github.com/JdeRobot/DL-Studio
https://github.com/JdeRobot/DeepLearningStudio
https://github.com/JoegameZhou/Ultra-Fast-Lane-Detection
Ultra Fast Deep Lane Detection with Hybrid Anchor Driven Ordinal Classification
https://github.com/JungSeokWoo/Lightweight-LaneDetection
Towards Lightweight Lane Detection by Optimizing Spatial Embedding
https://github.com/M155K4R4/autopilot
https://github.com/MalayAgarwal-Lee/SteeringWheelAnglePredictor
https://github.com/MarkRoy8888/CarND-Project-4-Behavioral-Cloning
https://github.com/MaybeShewill-CV/MNN-LaneNet
Towards End-to-End Lane Detection: an Instance Segmentation Approach
https://github.com/MaybeShewill-CV/lanenet-lane-detection
Towards End-to-End Lane Detection: an Instance Segmentation Approach
https://github.com/Meffazm/Lane-Detector
Towards End-to-End Lane Detection: an Instance Segmentation Approach
https://github.com/Mehul27/Self-Driving-Car
https://github.com/MisterTarock/Ultracar
https://github.com/Mohamed-ElhajAbdou/Self-driving-car
https://github.com/Mrjaggu/Self_driving_car
https://github.com/NOHYC/autonomous_driving_car_project
Learning Lightweight Lane Detection CNNs by Self Attention Distillation
https://github.com/NaturalHistoryMuseum/semantic-segmentation
Semantic Instance Segmentation with a Discriminative Loss Function
https://github.com/Naveenking006/AutoPilot
https://github.com/NickLucche/lane-detection
Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks
https://github.com/Nilanjan96/Self-Driving-Car
https://github.com/Noep1997/self-driving-car
https://github.com/Nuclearstar/End-to-End-Learning-for-Self-Driving-Cars
https://github.com/OpenDriveLab/OpenLane
PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark
https://github.com/PINTO0309/PINTO_model_zoo/tree/main/326_YOLOPv2
YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception
https://github.com/PankajKarki/Self-Driving-Car
https://github.com/RDXiaoLu/DLNet
https://github.com/RoyMachineLearning/Deep-Learning-Self-Driving-Simulator
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.