A teacher-student framework with Beta-confidence maps and spatial clipping produces pseudo-labels that improve online HD mapping by +6.1 mAP using only 16.5% labeled data.
IEEE Open Journal of Intelligent Transportation Systems4, 527–550 (2023) 1
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PseudoMapLabeler: Confidence-Aware Pseudo-Label Generation for Semi-Supervised Online Mapping
A teacher-student framework with Beta-confidence maps and spatial clipping produces pseudo-labels that improve online HD mapping by +6.1 mAP using only 16.5% labeled data.