most citedCARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.CV2022★ 2 cited

CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains

Julian Gebele, Bonifaz Stuhr, Johann Haselberger

Unsupervised Domain Adaptation demonstrates great potential to mitigate domain shifts by transferring models from labeled source domains to unlabeled target domains. While Unsuperv…