wongkwan / simple-effective-3dpose-baseline

My own Gluon reimplement of "A simple yet effective baseline for 3d human pose estimation"

A simple yet effective baseline for 3D human pose estimation

My own Gluon reimplement of A simple yet effective baseline for 3D human pose estimation
Here is the original implementation

Todo:

• Provide trained model
  
• Provide results on 2D pose estimates as input

Enviroments

python 3.7
mxnet-cu90 1.4.0
CUDA 9.0

Dependency

pip install pyyaml
pip install scipy
pip install matplotlib
pip install easydict

Dataset

1. Baidu Disk (code: kfsm) or Google Drive to download the HM3.6M annotation
2. Unzip data under data folder, and organize like this

${PROJECT_ROOT}
    `--data
        `--annot
            `--s_01_act_02_subact_01_ca_01
            `--s_01_act_02_subact_01_ca_02
            `-- ......
            `-- ......
            `-- ......
            `--s_11_act_16_subact_02_ca_04            

How-to-use

You can download my trained model from Google Drive, which MPJPE is 44.9mm.

usage: train.py/test.py [-h] --gpu GPU --root ROOT --dataset DATASET [--model MODEL]
                        [--debug DEBUG]

optional arguments:
  -h, --help         show this help message and exit
  --gpu GPU          GPUs to use, e.g. 0,1,2,3
  --root ROOT        /path/to/project/root/
  --dataset DATASET  /path/to/your/dataset/root/
  --model MODEL      /path/to/your/model/, to specify only when test
  --debug DEBUG      debug mode

Train: python train.py --root /project-root --gpu /gpu-to-use

Test: python test.py --root /project-root --gpu /gpu-to-use --model /model-path

PS: You can modify default configurations in config.py. Because it's a quite simple system, not many hyperparameters need to be tuned.

Results

Since I don't have 2D pose estimate results on HM3.6M, I just experiment with 2D ground truth as input. My best result is 44.9mm(no augment is used), slightly better than 45.5mm reported by paper.

Method	Avg	Direct	Discuss	Eating	Greet	Phone	Photo	Pose	Purch	Sitting	SittingD	Smoke	Wait	WaitD	Walk	WalkT
My Result	44.9	36.8	43.5	40.5	43.0	46.2	54.7	40.0	43.6	52.9	59.7	44.2	44.5	45.0	34.6	37.3
Paper	45.5	37.7	44.4	40.3	42.1	48.2	54.9	44.4	42.1	54.6	58.0	45.1	46.4	47.6	36.4	40.4