human-pose-estimation-3d-0001¶

Use Case and High-Level Description¶

Multi-person 3D human pose estimation model based on the Lightweight OpenPose and Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB papers.

Example¶

_images/human-pose-estimation-3d-0001.jpg

Specification¶

Metric	Value
MPJPE (mm)	100.45
GFlops	18.998
MParams	5.074
Source framework	PyTorch*

Inputs¶

Image, name: data, shape: 1, 3, 256, 448 in the B, C, H, W format, where:

B - batch size
C - number of channels
H - image height
W - image width

Expected color order is BGR.

Outputs¶

The net outputs are three blobs:

Name: features, shape: 1, 57, 32, 56 - coordinates in 3D space.
Name: heatmaps, shape: 1, 19, 32, 56 - keypoint heatmaps.
Name: pafs, shape: 1, 38, 32, 56 - keypoint pairwise relations (part affinity fields).

Download a Model and Convert it into OpenVINO™ IR Format¶

You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

omz_downloader --name <model_name>

An example of using the Model Converter:

omz_converter --name <model_name>

Demo usage¶

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

3D Human Pose Estimation Python\* Demo

Legal Information¶

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0.txt.

[*] Other names and brands may be claimed as the property of others.