[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
- Provide minimal implementation of RLE loss.
- Add model zoo.
- Provide implementation on Human3.6M dataset.
- Provide implementation on COCO dataset.
- Install pytorch >= 1.1.0 following official instruction.
- Install
rlepose
:
pip install cython
python setup.py develop
- Install COCOAPI.
pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
- Init
data
directory:
mkdir data
|-- 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
| |-- ...
|-- mpii
| |-- annotations
| | `-- annot_mpii.json
| `-- images
|-- 000001163.jpg
|-- 000003072.jpg
|-- 000004812.jpg
|--- ...
|-- h36m
`-- |-- annotations
| |-- Sample_trainmin_train_Human36M_protocol_2.json
| `-- Sample_64_test_Human36M_protocol_2.json
`-- images
|-- s_01_act_02_subact_01_ca_01
| |-- ...
|-- s_01_act_02_subact_01_ca_02
| |-- ...
`-- ...
./scripts/train.sh ./configs/256x192_res50_regress-flow.yaml train_rle_coco
./scripts/train.sh ./configs/256x192_res50_3d_h36mmpii-flow.yaml train_rle_h36m
Download the pretrained model from Google Drive.
./scripts/validate.sh ./configs/256x192_res50_regress-flow.yaml ./coco-laplace-rle.pth
Download the pretrained model from Google Drive.
./scripts/validate.sh ./configs/256x192_res50_3d_h36mmpii-flow.yaml ./h36m-laplace-rle.pth
If our code helps your research, please consider citing the following paper:
@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}
}