3D Human Pose Estimation On Total Capture

Metriken

Average MPJPE (mm)

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
ROS node wrapping	112	3D Human Pose Estimation in RGBD Images for Robotic Task Learning
PVH	107	Total capture: 3D human pose estimation fusing video and inertial sensors
Tri-CPM	99	Convolutional Pose Machines
IMUPVH	70	Total capture: 3D human pose estimation fusing video and inertial sensors
Single-RPSM	41.0	Cross View Fusion for 3D Human Pose Estimation
AutoEnc	35	Deep Autoencoder for Combined Human Pose Estimation and body Model Upscaling
DeepFuse-Vision Only	32.7	DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image
MTF-Transformer (M=0.4, T=7)	29.2	Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
Fusion-RPSM	29.0	Cross View Fusion for 3D Human Pose Estimation
DeepFuse-IMU	28.9	DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image
LWCDR	27.5	Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation
GeoFuse	24.6	Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach
AdaDeepFuse	22.5	FusePose: IMU-Vision Sensor Fusion in Kinematic Space for Parametric Human Pose Estimation
AdaFuse	19.2	AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild

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3D Human Pose Estimation On Total Capture | SOTA | HyperAI