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.
Ultra fast structure-aware deep lane detection
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
A PPO policy trained in Isaac Sim with domain randomization balances and steers a bicycle in sim (99.9% success) and transfers to real hardware.
citing papers explorer
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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.
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CycleRL: Sim-to-Real Deep Reinforcement Learning for Robust Autonomous Bicycle Control
A PPO policy trained in Isaac Sim with domain randomization balances and steers a bicycle in sim (99.9% success) and transfers to real hardware.