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Found 2 papers, 2 papers with code
Contrastive Learning for Lane Detection via Cross-Similarity
CLLD is a novel multitask contrastive learning that trains lane detection approaches to detect lane markings even in low visible situations by integrating local feature contrastive learning (CL) with our new proposed operation cross-similarity.
Ranked #4 on
Lane Detection
on TuSimple
3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane Detection
Lane detection is one of the most fundamental tasks for autonomous driving.
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