[Re] CLRNet: Cross Layer Refinement Network for Lane Detection

TL;DR

This paper provides a reproducibility report for CLRNet, a novel lane detection network that leverages multi-level features and claims to achieve state-of-the-art results on multiple benchmarks.

Contribution

It offers a reproducibility assessment of CLRNet, highlighting its innovative use of cross-layer feature refinement for improved lane detection performance.

Findings

Achieves state-of-the-art results on three benchmarks

Utilizes both high and low level features effectively

Reproducibility confirmed with available code

Abstract

The following work is a reproducibility report for CLRNet: Cross Layer Refinement Network for Lane Detection. The basic code was made available by the author. The paper proposes a novel Cross Layer Refinement Network to utilize both high and low level features for lane detection. The authors assert that the proposed technique sets the new state-of-the-art on three lane-detection benchmarks