mmhuman3d
OpenMMLab 3D Human Parametric Model Toolbox and Benchmark
Science Score: 54.0%
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3 of 35 committers (8.6%) from academic institutions -
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Low similarity (14.9%) to scientific vocabulary
Keywords from Contributors
Repository
OpenMMLab 3D Human Parametric Model Toolbox and Benchmark
Basic Info
- Host: GitHub
- Owner: open-mmlab
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://mmhuman3d.readthedocs.io/
- Size: 4.04 MB
Statistics
- Stars: 1,359
- Watchers: 25
- Forks: 149
- Open Issues: 133
- Releases: 9
Metadata Files
README.md
Introduction
English | 简体中文
MMHuman3D is an open-source PyTorch-based codebase for the use of 3D human parametric models in computer vision and computer graphics. It is a part of the OpenMMLab project.
The main branch works with PyTorch 1.7+.
If you are interested in multi-view motion capture, please refer to XRMoCap for more details.
https://user-images.githubusercontent.com/62529255/144362861-e794b404-c48f-4ebe-b4de-b91c3fbbaa3b.mp4
Major Features
- Reproducing popular methods with a modular framework
MMHuman3D reimplements popular methods, allowing users to reproduce SOTAs with one line of code. The modular framework is convenient for rapid prototyping: the users may attempt various hyperparameter settings and even network architectures, without actually modifying the code.
- Supporting various datasets with a unified data convention
With the help of a convention toolbox, a unified data format HumanData is used to align all supported datasets. Preprocessed data files are also available.
- Versatile visualization toolbox
A suite of differential visualization tools for human parametric model rendering (including part segmentation, depth map and point clouds) and conventional 2D/3D keypoints are available.
News
- 2023-04-05: MMHuman3D v0.11.0 is released. Major updates include:
- 2022-10-12: MMHuman3D v0.10.0 is released. Major updates include:
- Add webcam demo and real-time renderer
- Update dataloader to speed up training
- Add balanced MSE loss for imbalanced HMR training
- 2022-07-08: MMHuman3D v0.9.0 is released. Major updates include:
Benchmark and Model Zoo
More details can be found in model_zoo.md.
Supported body models:
(click to collapse)
- [x] [SMPL](https://smpl.is.tue.mpg.de/) (SIGGRAPH Asia'2015) - [x] [SMPL-X](https://smpl-x.is.tue.mpg.de/) (CVPR'2019) - [x] [MANO](https://mano.is.tue.mpg.de/) (SIGGRAPH ASIA'2017) - [x] [FLAME](https://flame.is.tue.mpg.de/) (SIGGRAPH ASIA'2017) - [x] [STAR](https://star.is.tue.mpg.de/) (ECCV'2020)Supported methods:
(click to collapse)
- [x] [SMPLify](https://smplify.is.tue.mpg.de/) (ECCV'2016) - [x] [SMPLify-X](https://smpl-x.is.tue.mpg.de/) (CVPR'2019) - [x] [HMR](https://akanazawa.github.io/hmr/) (CVPR'2018) - [x] [SPIN](https://www.seas.upenn.edu/~nkolot/projects/spin/) (ICCV'2019) - [x] [VIBE](https://github.com/mkocabas/VIBE) (CVPR'2020) - [x] [HybrIK](https://jeffli.site/HybrIK/) (CVPR'2021) - [x] [PARE](https://pare.is.tue.mpg.de/) (ICCV'2021) - [x] [DeciWatch](https://ailingzeng.site/deciwatch) (ECCV'2022) - [x] [SmoothNet](https://ailingzeng.site/smoothnet) (ECCV'2022) - [x] [ExPose](https://expose.is.tue.mpg.de) (ECCV'2020) - [x] [BalancedMSE](https://sites.google.com/view/balanced-mse/home) (CVPR'2022) - [x] [PyMAF-X](https://www.liuyebin.com/pymaf-x/) (arXiv'2022) - [x] [ExPose](configs/expose) (ECCV'2020) - [x] [PyMAF-X](configs/pymafx) (arXiv'2022) - [x] [CLIFF](configs/cliff) (ECCV'2022)Supported datasets:
(click to collapse)
- [x] [3DPW](https://virtualhumans.mpi-inf.mpg.de/3DPW/) (ECCV'2018) - [x] [AGORA](https://agora.is.tue.mpg.de/) (CVPR'2021) - [x] [AMASS](https://amass.is.tue.mpg.de/) (ICCV'2019) - [x] [COCO](https://cocodataset.org/#home) (ECCV'2014) - [x] [COCO-WholeBody](https://github.com/jin-s13/COCO-WholeBody) (ECCV'2020) - [x] [CrowdPose](https://github.com/Jeff-sjtu/CrowdPose) (CVPR'2019) - [x] [EFT](https://github.com/facebookresearch/eft) (3DV'2021) - [x] [GTA-Human](https://caizhongang.github.io/projects/GTA-Human/) (arXiv'2021) - [x] [Human3.6M](http://vision.imar.ro/human3.6m/description.php) (TPAMI'2014) - [x] [InstaVariety](https://github.com/akanazawa/human_dynamics/blob/master/doc/insta_variety.md) (CVPR'2019) - [x] [LSP](https://sam.johnson.io/research/lsp.html) (BMVC'2010) - [x] [LSP-Extended](https://sam.johnson.io/research/lspet.html) (CVPR'2011) - [x] [MPI-INF-3DHP](http://gvv.mpi-inf.mpg.de/3dhp-dataset/) (3DC'2017) - [x] [MPII](http://human-pose.mpi-inf.mpg.de/) (CVPR'2014) - [x] [Penn Action](http://dreamdragon.github.io/PennAction/) (ICCV'2012) - [x] [PoseTrack18](https://posetrack.net/users/download.php) (CVPR'2018) - [x] [SURREAL](https://www.di.ens.fr/willow/research/surreal/data/) (CVPR'2017) - [x] [UP3D](https://files.is.tuebingen.mpg.de/classner/up/) (CVPR'2017) - [x] [FreiHand](https://lmb.informatik.uni-freiburg.de/projects/freihand/) (ICCV'2019) - [x] [EHF](https://smpl-x.is.tue.mpg.de/) (CVPR'2019) - [x] [Stirling/ESRC-Face3D](http://pics.psych.stir.ac.uk/ESRC/index.htm) (FG'2018)We will keep up with the latest progress of the community, and support more popular methods and frameworks.
If you have any feature requests, please feel free to leave a comment in the wishlist.
Get Started
Please see getting_started.md for the basic usage of MMHuman3D.
License
This project is released under the Apache 2.0 license. Some supported methods may carry additional licenses.
Citation
If you find this project useful in your research, please consider citing:
bibtex
@misc{mmhuman3d,
title={OpenMMLab 3D Human Parametric Model Toolbox and Benchmark},
author={MMHuman3D Contributors},
howpublished = {\url{https://github.com/open-mmlab/mmhuman3d}},
year={2021}
}
Contributing
We appreciate all contributions to improve MMHuman3D. Please refer to CONTRIBUTING.md for the contributing guideline.
Acknowledgement
MMHuman3D is an open source project that is contributed by researchers and engineers from both the academia and the industry. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedback. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models.
Projects in OpenMMLab
- MMCV: OpenMMLab foundational library for computer vision.
- MIM: MIM Installs OpenMMLab Packages.
- MMClassification: OpenMMLab image classification toolbox and benchmark.
- MMDetection: OpenMMLab detection toolbox and benchmark.
- MMDetection3D: OpenMMLab next-generation platform for general 3D object detection.
- MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
- MMAction2: OpenMMLab next-generation action understanding toolbox and benchmark.
- MMTracking: OpenMMLab video perception toolbox and benchmark.
- MMPose: OpenMMLab pose estimation toolbox and benchmark.
- MMEditing: OpenMMLab image and video editing toolbox.
- MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding.
- MMGeneration: OpenMMLab next-generation toolbox for generative models.
- MMFlow: OpenMMLab optical flow toolbox and benchmark.
- MMFewShot: OpenMMLab FewShot Learning Toolbox and Benchmark.
- MMHuman3D: OpenMMLab 3D Human Parametric Model Toolbox and Benchmark.
- MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
- MMRazor: OpenMMLab model compression toolbox and benchmark.
- MMDeploy: OpenMMLab model deployment framework.
Owner
- Name: OpenMMLab
- Login: open-mmlab
- Kind: organization
- Location: China
- Website: https://openmmlab.com
- Twitter: OpenMMLab
- Repositories: 53
- Profile: https://github.com/open-mmlab
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - name: "MMHuman3D Contributors" title: "MMHuman3D: OpenMMLab 3D Human Parametric Model Toolbox and Benchmark" date-released: 2021-12-01 url: "https://github.com/open-mmlab/mmhuman3d" license: Apache-2.0
GitHub Events
Total
- Issues event: 4
- Watch event: 143
- Issue comment event: 1
- Push event: 11
- Fork event: 17
Last Year
- Issues event: 4
- Watch event: 143
- Issue comment event: 1
- Push event: 11
- Fork event: 17
Committers
Last synced: 12 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| LazyBusyYang | g****n@o****m | 39 |
| Zhongang Cai | 6****g | 34 |
| pangyyyyy | p****6@g****m | 33 |
| Lei Yang | y****v@g****m | 32 |
| ttxskk | s****s@g****m | 22 |
| JasonBoy1 | w****2@1****m | 20 |
| mingyuan-zhang | z****8@g****m | 15 |
| Jacob_Liu | s****u@s****h | 6 |
| jiaqiAA | 6****A | 5 |
| LengYue | l****e@l****e | 3 |
| Tyler Luan | t****n@1****m | 3 |
| Wenjia Wang | 3****1 | 3 |
| Xuan Ju | 8****7 | 3 |
| Daxuan | K****7@h****m | 3 |
| oneScotch | 7****h | 2 |
| Zhu Shuai | z****3@1****m | 2 |
| Shannon | 7****s | 2 |
| rshaojimmy | r****o@l****k | 1 |
| Haofan Wang | h****i@g****m | 1 |
| zhengjie.xu | j****e@g****m | 1 |
| wooil | p****i@g****m | 1 |
| wendaizhou | 5****u | 1 |
| liuzhe | 5****1 | 1 |
| innerlee | 3****0@q****m | 1 |
| ailingzengzzz | a****z@g****m | 1 |
| ZHELUN SHI | 4****7 | 1 |
| Yunfeng Wang | v****a | 1 |
| Yongtao Ge | y****e@a****u | 1 |
| Yining Li | l****2@g****m | 1 |
| Yinghao Zhu | y****9@g****m | 1 |
| and 5 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 7 months ago
All Time
- Total issues: 102
- Total pull requests: 61
- Average time to close issues: about 1 month
- Average time to close pull requests: about 1 month
- Total issue authors: 73
- Total pull request authors: 24
- Average comments per issue: 1.67
- Average comments per pull request: 1.43
- Merged pull requests: 37
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 8
- Pull requests: 1
- Average time to close issues: 6 days
- Average time to close pull requests: 2 days
- Issue authors: 6
- Pull request authors: 1
- Average comments per issue: 0.25
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- lucasjinreal (8)
- flyyyyer (5)
- felixshing (4)
- shihzenq (3)
- SWWdz (3)
- gjmm07 (3)
- github1838 (2)
- Dipankar1997161 (2)
- luohao123 (2)
- zhewei-mt (2)
- Darius-H (2)
- PMPBinZhang (2)
- ChennyDeng (2)
- WenjiaWang0312 (2)
- yuchen-ji (2)
Pull Request Authors
- caizhongang (8)
- Wei-Chen-hub (6)
- oneScotch (6)
- ttxskk (6)
- JacobLiu-S (6)
- jiaqiAA (5)
- pangyyyyy (3)
- Zessay (2)
- yhzhu99 (2)
- WenjiaWang0312 (2)
- crazysteeaam (2)
- Naive-Bayes (2)
- wendaizhou (1)
- vra (1)
- Fubuki901 (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
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Total downloads:
- pypi 182 last-month
-
Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 1
(may contain duplicates) - Total versions: 18
- Total maintainers: 1
proxy.golang.org: github.com/open-mmlab/mmhuman3d
- Documentation: https://pkg.go.dev/github.com/open-mmlab/mmhuman3d#section-documentation
- License: apache-2.0
-
Latest release: v0.11.0
published almost 3 years ago
Rankings
pypi.org: mmhuman3d
OpenMMLab 3D Human Parametric Model Toolbox and Benchmark
- Homepage: https://github.com/open-mmlab/mmhuman3d
- Documentation: https://mmhuman3d.readthedocs.io/
- License: Apache License 2.0
-
Latest release: 0.11.0
published almost 3 years ago
Rankings
Maintainers (1)
Dependencies
- docutils ==0.16.0
- myst-parser *
- sphinx ==4.0.2
- sphinx-copybutton *
- sphinx_markdown_tables *
- sphinx_rtd_theme ==0.5.2
- mmcv *
- torch *
- torchvision *
- astropy *
- cdflib <0.4.0
- chumpy *
- colormap *
- easydev *
- h5py *
- matplotlib *
- numpy *
- opencv-python *
- pandas *
- pickle5 *
- scikit-image *
- scipy *
- smplx *
- tqdm *
- vedo *
- codecov *
- flake8 *
- interrogate *
- isort ==4.3.21
- pytest *
- xdoctest >=0.10.0
- yapf *
- actions/checkout v2 composite
- codecov/codecov-action v2 composite
- conda-incubator/setup-miniconda v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-python v1 composite