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3D Human Pose Estimation On Total Capture

Metrics

Average MPJPE (mm)

Results

Performance results of various models on this benchmark

Paper Title
ROS node wrapping1123D Human Pose Estimation in RGBD Images for Robotic Task Learning
PVH107Total capture: 3D human pose estimation fusing video and inertial sensors
Tri-CPM99Convolutional Pose Machines
IMUPVH70Total capture: 3D human pose estimation fusing video and inertial sensors
Single-RPSM41.0Cross View Fusion for 3D Human Pose Estimation
AutoEnc35Deep Autoencoder for Combined Human Pose Estimation and body Model Upscaling
DeepFuse-Vision Only32.7DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image
MTF-Transformer (M=0.4, T=7)29.2Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
Fusion-RPSM29.0Cross View Fusion for 3D Human Pose Estimation
DeepFuse-IMU28.9DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image
LWCDR27.5Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation
GeoFuse24.6Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach
AdaDeepFuse22.5FusePose: IMU-Vision Sensor Fusion in Kinematic Space for Parametric Human Pose Estimation
AdaFuse19.2AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild
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3D Human Pose Estimation On Total Capture | SOTA | HyperAI