Environmental illusions cause 5-7% accuracy drops in lane detection models and can trigger collisions in closed-loop simulation, with a proposed defense (MIDA) recovering ~4% robustness.
Curvelane-nas: Unifying lane-sensitive architecture search and adaptive point blending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2representative citing papers
GFSR introduces LCC for geometric fidelity calibration via LaneIoU and CRI, plus AGLR for gated point refinement, reporting SOTA F1 scores of 81.46% and 65.01% on CULane and 87.35% on CurveLanes.
citing papers explorer
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Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective
Environmental illusions cause 5-7% accuracy drops in lane detection models and can trigger collisions in closed-loop simulation, with a proposed defense (MIDA) recovering ~4% robustness.
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GFSR: Geometric Fidelity and Spatial Refinement for Reliable Lane Detection
GFSR introduces LCC for geometric fidelity calibration via LaneIoU and CRI, plus AGLR for gated point refinement, reporting SOTA F1 scores of 81.46% and 65.01% on CULane and 87.35% on CurveLanes.