Package: mmhuman3d
IntroductionEnglish |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 theOpenMMLabproject.The main branch works withPyTorch 1.7+.If you are interested in multi-view motion capture, please refer toXRMoCapfor more details.https://user-images.githubusercontent.com/62529255/144362861-e794b404-c48f-4ebe-b4de-b91c3fbbaa3b.mp4Major FeaturesReproducing popular methods with a modular frameworkMMHuman3D 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 conventionWith the help of a convention toolbox, a unified data formatHumanDatais used to align all supported datasets. Preprocessed data files are also available.Versatile visualization toolboxA suite of differentiale visualization tools for human parametric model rendering (including part segmentation, depth map and point clouds) and conventional 2D/3D keypoints are available.News2023-04-05: MMHuman3Dv0.11.0is released. Major updates include:AddExPoseinferenceAddPyMAF-XinferenceSupportCLIFF2022-10-12: MMHuman3Dv0.10.0is released. Major updates include:Add webcam demo and real-time rendererUpdate dataloader to speed up trainingAddbalanced MSEloss for imbalanced HMR training2022-07-08: MMHuman3Dv0.9.0is released. Major updates include:Support SMPL-X estimation withExPosefor simultaneous recovery of face, hands and bodySupport new body modelSTARRelease ofGTA-Humandataset with SPIN-FT (51.98 mm) and PARE-FT (46.84 mm) baselines! (Official)Refactor registration and improve performance of SPIN to 57.54 mmBenchmark and Model ZooMore details can be found inmodel_zoo.md.Supported body models:(click to collapse)SMPL(SIGGRAPH Asia'2015)SMPL-X(CVPR'2019)MANO(SIGGRAPH ASIA'2017)FLAME(SIGGRAPH ASIA'2017)STAR(ECCV'2020)Supported methods:(click to collapse)SMPLify(ECCV'2016)SMPLify-X(CVPR'2019)HMR(CVPR'2018)SPIN(ICCV'2019)VIBE(CVPR'2020)HybrIK(CVPR'2021)PARE(ICCV'2021)DeciWatch(ECCV'2022)SmoothNet(ECCV'2022)ExPose(ECCV'2020)BalancedMSE(CVPR'2022)PyMAF-X(arXiv'2022)ExPose(ECCV'2020)PyMAF-X(arXiv'2022)CLIFF(ECCV'2022)Supported datasets:(click to collapse)3DPW(ECCV'2018)AGORA(CVPR'2021)AMASS(ICCV'2019)COCO(ECCV'2014)COCO-WholeBody(ECCV'2020)CrowdPose(CVPR'2019)EFT(3DV'2021)GTA-Human(arXiv'2021)Human3.6M(TPAMI'2014)InstaVariety(CVPR'2019)LSP(BMVC'2010)LSP-Extended(CVPR'2011)MPI-INF-3DHP(3DC'2017)MPII(CVPR'2014)Penn Action(ICCV'2012)PoseTrack18(CVPR'2018)SURREAL(CVPR'2017)UP3D(CVPR'2017)FreiHand(ICCV'2019)EHF(CVPR'2019)Stirling/ESRC-Face3D(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 thewishlist.Get StartedPlease seegetting_started.mdfor the basic usage of MMHuman3D.LicenseThis project is released under theApache 2.0 license. Some supported methods may carryadditional licenses.CitationIf you find this project useful in your research, please consider cite:@misc{mmhuman3d,title={OpenMMLab 3D Human Parametric Model Toolbox and Benchmark},author={MMHuman3D Contributors},howpublished={\url{https://github.com/open-mmlab/mmhuman3d}},year={2021}}ContributingWe appreciate all contributions to improve MMHuman3D. Please refer toCONTRIBUTING.mdfor the contributing guideline.AcknowledgementMMHuman3D 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 feedbacks.
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 OpenMMLabMMCV: 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.