Log In Sign Up

Towards Lightweight Lane Detection by Optimizing Spatial Embedding

by   Seokwoo Jung, et al.

A number of lane detection methods depend on a proposal-free instance segmentation because of its adaptability to flexible object shape, occlusion, and real-time application. This paper addresses the problem that pixel embedding in proposal-free instance segmentation based lane detection is difficult to optimize. A translation invariance of convolution, which is one of the supposed strengths, causes challenges in optimizing pixel embedding. In this work, we propose a lane detection method based on proposal-free instance segmentation, directly optimizing spatial embedding of pixels using image coordinate. Our proposed method allows the post-processing step for center localization and optimizes clustering in an end-to-end manner. The proposed method enables real-time lane detection through the simplicity of post-processing and the adoption of a lightweight backbone. Our proposed method demonstrates competitive performance on public lane detection datasets.


Key Points Estimation and Point Instance Segmentation Approach for Lane Detection

State-of-the-art lane detection methods achieve successful performance. ...

Learning to Cluster for Proposal-Free Instance Segmentation

This work proposed a novel learning objective to train a deep neural net...

LaneAF: Robust Multi-Lane Detection with Affinity Fields

This study presents an approach to lane detection involving the predicti...

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

Modern cars are incorporating an increasing number of driver assist feat...

Instance segmentation with the number of clusters incorporated in embedding learning

Semantic and instance segmentation algorithms are two general yet distin...

Reinforced Coloring for End-to-End Instance Segmentation

Instance segmentation is one of the actively studied research topics in ...

RCLane: Relay Chain Prediction for Lane Detection

Lane detection is an important component of many real-world autonomous s...

Code Repositories