[Re] CLRNet: Cross Layer Refinement Network for Lane Detection
Viswesh N, Kaushal Jadhav, Avi Amalanshu, Bratin Mondal, Sabaris Waran, Om Sadhwani, Apoorv Kumar, Debashish Chakravarty
arXiv:2310.01142v11 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis
This is an incremental reproducibility study for lane detection in autonomous driving.
The paper reproduces CLRNet, a cross-layer refinement network for lane detection that uses high and low-level features, achieving state-of-the-art results on three benchmarks.
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