A YOLO keypoint model trained on 37k+ public images plus 1k neonatal frames achieves SOTA NME and low failure rates for 68-point neonatal landmark detection in clinical conditions.
One millisecond face alignment with an ensemble of regression trees
2 Pith papers cite this work. Polarity classification is still indexing.
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Bengal-HP_RU is the first publicly available head pose dataset for Bengali subjects, with 12,894 images collected from Wikimedia Commons and partitioned by uploader identity.
citing papers explorer
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NeoLoc-68: End-to-end 68-point neonatal facial landmark localisation in neonatal clinical environments
A YOLO keypoint model trained on 37k+ public images plus 1k neonatal frames achieves SOTA NME and low failure rates for 68-point neonatal landmark detection in clinical conditions.
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Bengal-HP_RU: A Dataset of Bengal People For Head Pose Estimation
Bengal-HP_RU is the first publicly available head pose dataset for Bengali subjects, with 12,894 images collected from Wikimedia Commons and partitioned by uploader identity.