HyperAI

Keypoint Detection On Coco Test Dev

Métriques

AP
APL
APM

Résultats

Résultats de performance de divers modèles sur ce benchmark

Tableau comparatif
Nom du modèleAPAPLAPM
openpifpaf-composite-fields-for-semantic70.976.867.1
towards-accurate-multi-person-pose-estimation-70.062.3
simple-baselines-for-human-pose-estimation-80.070.3
cascaded-pyramid-network-for-multi-person-77.268.7
deep-high-resolution-representation-learning-81.571.9
mask-r-cnn-71.457.8
rmpe-regional-multi-person-pose-estimation-81.5-
simple-pose-rethinking-and-improving-a-bottom68.170.566.8
directpose-direct-end-to-end-multi-person64.871.560.4
simple-baselines-for-human-pose-estimation-82.773.0
cascaded-pyramid-network-for-multi-person-78.169.5
rethinking-on-multi-stage-networks-for-human76.181.572.3
realtime-multi-person-2d-pose-estimation-68.257.1
deep-high-resolution-representation-learning-83.173.4
associative-embedding-end-to-end-learning-for-72.660.6
pifpaf-composite-fields-for-human-pose66.472.162.6