RLE(Residual-Log-likelihood-Estimation) with COCO Human Pose Video Demo

Result Example

Video Demo Example

Quick Start

1. Install pytorch >= 1.1.0 following official instruction.

2. Install rlepose:

pip install cython
python setup.py develop

3. Install COCOAPI.

pip install pycocotools

4. Init data directory:

mkdir data

5. Download COCO data, MPII (annotations) and Human3.6M data (from PoseNet or ours):

|-- data
`-- |-- coco
    |   |-- annotations
    |   |   |-- person_keypoints_train2017.json
    |   |   `-- person_keypoints_val2017.json
    |   `-- images
    |       |-- train2017
    |       |   |-- 000000000009.jpg
    |       |   |-- 000000000025.jpg
    |       |   |-- 000000000030.jpg
    |       |   |-- ... 
    |       `-- val2017
    |           |-- 000000000139.jpg
    |           |-- 000000000285.jpg
    |           |-- 000000000632.jpg
    `--           |-- ... 

Training

Train on MSCOCO

./scripts/train.sh ./configs/256x192_res50_regress-flow.yaml train_rle_coco

Evaluation

Validate on MSCOCO

Download the pretrained model from Google Drive.

./scripts/validate.sh ./configs/256x192_res50_regress-flow.yaml ./coco-laplace-rle.pth

Demo

1. Config like this figure

Running Script Env Config

Or you can directly copy this

--cfg
../configs/256x192_res50_regress-flow.yaml
--valid-batch
1
--checkpoint
../coco-laplace-rle.pth
--launcher
pytorch
--rank
0

2. Customize you video path in demo_video.py line 56.

Customize video path

Information about RLE

[Paper] [arXiv] [Project Page]

Human Pose Regression with Residual Log-likelihood Estimation
Jiefeng Li, Siyuan Bian, Ailing Zeng, Can Wang, Bo Pang, Wentao Liu, Cewu Lu
ICCV 2021 Oral

Regression with Residual Log-likelihood Estimation

Acknowledgment

@inproceedings{li2021human,
    title={Human Pose Regression with Residual Log-likelihood Estimation},
    author={Li, Jiefeng and Bian, Siyuan and Zeng, Ailing and Wang, Can and Pang, Bo and Liu, Wentao and Lu, Cewu},
    booktitle={ICCV},
    year={2021}
}

Contact

[email protected]