An accurate High Definition (HD) Maps with lane markings usually serves as the back-end for all
commercial auto-drive vehicles for navigation. Currently, most HD maps are constructed manually by
human labelers. In this challenge, we require participants to develop algorithms to extract all
basic road elements from RGB image frames. The segmentation results can be directly used for HD Maps
construction or updating process.
This repository contains the evaluation scripts for the landmark detection challenge of the ApolloScapes dataset. This large-scale dataset contains a diverse set of stereo video sequences recorded in street scenes from different cities, with high quality pixel-level annotations of 110 000+ frames.