HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
3D Human Pose Estimation
3D Human Pose Estimation On Total Capture
3D Human Pose Estimation On Total Capture
Metrics
Average MPJPE (mm)
Results
Performance results of various models on this benchmark
Columns
Model Name
Average MPJPE (mm)
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
0 of 14 row(s) selected.
Previous
Next
3D Human Pose Estimation On Total Capture | SOTA | HyperAI