Structure Guided Lane Detection with python
Project for the IJCAI 2021 paper “Structure Guided Lane Detection”
Abstract
Recently, lane detection has made great progress
with the rapid development of deep neural networks
and autonomous driving. However, there
exist three mainly problems including characterizing
lanes, modeling the structural relationship between
scenes and lanes, and supporting more attributes
(e.g., instance and type) of lanes. In this
paper, we propose a novel structure guided framework
to solve these problems simultaneously. In
the framework, we first introduce a new lane representation
to characterize each instance. Then a topdown
vanishing point guided anchoring mechanism
is proposed to produce intensive anchors, which efficiently
capture various lanes. Next, multi-level
structural constraints are used to improve the perception
of lanes. In the process, pixel-level perception
with binary segmentation is introduced to
promote features around anchors and restore lane
details from bottom up, a lane-level relation is put
forward