Lane Detection

14 papers with code · Computer Vision
Subtask of Autonomous Vehicles

Lane detection is the task of detecting lanes on a road from a camera.

( Image credit: End-to-end Lane Detection )

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Latest papers with code

Copy-and-Paste Networks for Deep Video Inpainting

ICCV 2019 shleecs/Copy-and-Paste-Networks-for-Deep-Video-Inpainting

We propose a novel DNN-based framework called the Copy-and-Paste Networks for video inpainting that takes advantage of additional information in other frames of the video.

IMAGE INPAINTING LANE DETECTION VIDEO INPAINTING

36
30 Aug 2019

Learning Lightweight Lane Detection CNNs by Self Attention Distillation

ICCV 2019 cardwing/Codes-for-Lane-Detection

Training deep models for lane detection is challenging due to the very subtle and sparse supervisory signals inherent in lane annotations.

LANE DETECTION REPRESENTATION LEARNING

511
02 Aug 2019

Lane Detection and Classification using Cascaded CNNs

2 Jul 2019fabvio/Cascade-LD

Lane detection is extremely important for autonomous vehicles.

LANE DETECTION

17
02 Jul 2019

FastDraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network

CVPR 2019 jonahthelion/FastDraw

In this paper, we use lane detection to study modeling and training techniques that yield better performance on real world test drives.

LANE DETECTION STYLE TRANSFER

3
10 May 2019

Enhanced free space detection in multiple lanes based on single CNN with scene identification

2 May 2019fabvio/ld-lsi

Traditional algorithms usually estimate only the position of the lanes on the road, but an autonomous control system may also need to know if a lane marking can be crossed or not, and what portion of space inside the lane is free from obstacles, to make safer control decisions.

LANE DETECTION

36
02 May 2019

Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks

6 Mar 2019NickLucche/lane-detection

Specifically, information of each frame is abstracted by a CNN block, and the CNN features of multiple continuous frames, holding the property of time-series, are then fed into the RNN block for feature learning and lane prediction.

LANE DETECTION TIME SERIES

11
06 Mar 2019

End-to-end Lane Detection through Differentiable Least-Squares Fitting

1 Feb 2019wvangansbeke/LaneDetection_End2End

The problem with such a two-step approach is that the parameters of the network are not optimized for the true task of interest (estimating the lane curvature parameters) but for a proxy task (segmenting the lane markings), resulting in sub-optimal performance.

LANE DETECTION

334
01 Feb 2019

LaneNet: Real-Time Lane Detection Networks for Autonomous Driving

4 Jul 2018klintan/pytorch-lanenet

Lane detection is to detect lanes on the road and provide the accurate location and shape of each lane.

AUTONOMOUS DRIVING LANE DETECTION

38
04 Jul 2018

Learning to Cluster for Proposal-Free Instance Segmentation

17 Mar 2018GT-RIPL/L2C

We utilize the most fundamental property of instance labeling -- the pairwise relationship between pixels -- as the supervision to formulate the learning objective, then apply it to train a fully convolutional network (FCN) for learning to perform pixel-wise clustering.

AUTONOMOUS DRIVING INSTANCE SEGMENTATION LANE DETECTION OBJECT DETECTION SEMANTIC SEGMENTATION

179
17 Mar 2018

Towards End-to-End Lane Detection: an Instance Segmentation Approach

15 Feb 2018MaybeShewill-CV/lanenet-lane-detection

By doing so, we ensure a lane fitting which is robust against road plane changes, unlike existing approaches that rely on a fixed, pre-defined transformation.

INSTANCE SEGMENTATION LANE DETECTION SEMANTIC SEGMENTATION

934
15 Feb 2018