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3D Multi Person Pose Estimation On Campus

Metriken

Mean mAP

PCP3D

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Mean mAP	PCP3D	Paper Title	Repository
VTP	80.1	96.3	VTP: Volumetric Transformer for Multi-view Multi-person 3D Pose Estimation	-
TesseTrack	-	97.4	TesseTrack: End-to-End Learnable Multi-Person Articulated 3D Pose Tracking	-
PlaneSweepPose	-	97	Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo	-
Ershadi-Nasab model	-	90.6	Multiple human 3d pose estimation from multiview images	-
MvP	-	96.6	Direct Multi-view Multi-person 3D Pose Estimation	-
MVPose	-	96.3	Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views	-
Faster VoxelPose	-	96.9	Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection	-
VoxelTrack	-	96.7	VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wild	-
Belagiannis model v.3	-	84.5	3D Pictorial Structures Revisited: Multiple Human Pose Estimation	-
Belagiannis model v.2	-	78	Multiple human pose estimation with temporally consistent 3d pictorial structures	-
SmartEdgeSensor	-	97	Real-Time Multi-View 3D Human Pose Estimation using Semantic Feedback to Smart Edge Sensors	-
Part-aware Pose	-	96.79	Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking	-
VoxelPose	-	96.7	VoxelPose: Towards Multi-Camera 3D Human Pose Estimation in Wild Environment	-
UMMT	-	97.0	A Unified Multi-view Multi-person Tracking Framework	-
Cross-View	-	96.6	Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS	-
crossview_3d_pose_tracking	-	96.6	Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS	-

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3D Multi Person Pose Estimation On Campus | SOTA | HyperAI