{"id":13631892,"url":"https://github.com/YuliangXiu/ECON","last_synced_at":"2025-04-18T01:32:17.891Z","repository":{"id":64524391,"uuid":"544399418","full_name":"YuliangXiu/ECON","owner":"YuliangXiu","description":"[CVPR'23, Highlight] ECON: Explicit Clothed humans Optimized via Normal integration","archived":false,"fork":false,"pushed_at":"2024-09-17T21:59:40.000Z","size":232482,"stargazers_count":1102,"open_issues_count":38,"forks_count":107,"subscribers_count":30,"default_branch":"master","last_synced_at":"2024-10-29T15:29:19.481Z","etag":null,"topics":["3d-reconstruction","avatar-generator","computer-graphics","computer-vision","digital-twins","metaverse","normal-maps","pifu","pifuhd","smpl-body","smplx","virtual-humans"],"latest_commit_sha":null,"homepage":"https://xiuyuliang.cn/econ","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/YuliangXiu.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-10-02T11:33:33.000Z","updated_at":"2024-10-28T08:58:17.000Z","dependencies_parsed_at":"2024-10-14T10:51:04.744Z","dependency_job_id":null,"html_url":"https://github.com/YuliangXiu/ECON","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YuliangXiu%2FECON","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YuliangXiu%2FECON/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YuliangXiu%2FECON/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/YuliangXiu%2FECON/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/YuliangXiu","download_url":"https://codeload.github.com/YuliangXiu/ECON/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":223059713,"owners_count":17081243,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["3d-reconstruction","avatar-generator","computer-graphics","computer-vision","digital-twins","metaverse","normal-maps","pifu","pifuhd","smpl-body","smplx","virtual-humans"],"created_at":"2024-08-01T22:02:42.979Z","updated_at":"2024-11-09T00:30:27.748Z","avatar_url":"https://github.com/YuliangXiu.png","language":"Python","readme":"\u003c!-- PROJECT LOGO --\u003e\n\n\u003cp align=\"center\"\u003e\n\n  \u003ch1 align=\"center\"\u003eECON: Explicit Clothed humans Optimized via Normal integration\u003c/h1\u003e\n  \u003cp align=\"center\"\u003e\n    \u003ca href=\"http://xiuyuliang.cn/\"\u003e\u003cstrong\u003eYuliang Xiu\u003c/strong\u003e\u003c/a\u003e\n    ·\n    \u003ca href=\"https://ps.is.tuebingen.mpg.de/person/jyang\"\u003e\u003cstrong\u003eJinlong Yang\u003c/strong\u003e\u003c/a\u003e\n    ·\n    \u003ca href=\"https://hoshino042.github.io/homepage/\"\u003e\u003cstrong\u003eXu Cao\u003c/strong\u003e\u003c/a\u003e\n    ·\n    \u003ca href=\"https://ps.is.mpg.de/~dtzionas\"\u003e\u003cstrong\u003eDimitrios Tzionas\u003c/strong\u003e\u003c/a\u003e\n    ·\n    \u003ca href=\"https://ps.is.tuebingen.mpg.de/person/black\"\u003e\u003cstrong\u003eMichael J. Black\u003c/strong\u003e\u003c/a\u003e\n  \u003c/p\u003e\n  \u003ch2 align=\"center\"\u003eCVPR 2023 (Highlight)\u003c/h2\u003e\n  \u003cdiv align=\"center\"\u003e\n    \u003cimg src=\"./assets/teaser.gif\" alt=\"Logo\" width=\"100%\"\u003e\n  \u003c/div\u003e\n\n  \u003cp align=\"center\"\u003e\n  \u003cbr\u003e\n    \u003ca href=\"https://pytorch.org/get-started/locally/\"\u003e\u003cimg alt=\"PyTorch\" src=\"https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch\u0026logoColor=white\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://pytorchlightning.ai/\"\u003e\u003cimg alt=\"Lightning\" src=\"https://img.shields.io/badge/-Lightning-792ee5?logo=pytorchlightning\u0026logoColor=white\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://cupy.dev/\"\u003e\u003cimg alt=\"cupy\" src=\"https://img.shields.io/badge/-Cupy-46C02B?logo=numpy\u0026logoColor=white\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://twitter.com/yuliangxiu\"\u003e\u003cimg alt='Twitter' src=\"https://img.shields.io/twitter/follow/yuliangxiu?label=%40yuliangxiu\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://discord.gg/Vqa7KBGRyk\"\u003e\u003cimg alt=\"discord invitation link\" src=\"https://dcbadge.vercel.app/api/server/Vqa7KBGRyk?style=flat\"\u003e\u003c/a\u003e\n    \u003cbr\u003e\u003c/br\u003e\n    \u003ca href=\"https://arxiv.org/abs/2212.07422\"\u003e\n      \u003cimg src='https://img.shields.io/badge/Paper-PDF-green?style=for-the-badge\u0026logo=adobeacrobatreader\u0026logoWidth=20\u0026logoColor=white\u0026labelColor=66cc00\u0026color=94DD15' alt='Paper PDF'\u003e\n    \u003c/a\u003e\n    \u003ca href='https://xiuyuliang.cn/econ/'\u003e\n      \u003cimg src='https://img.shields.io/badge/ECON-Page-orange?style=for-the-badge\u0026logo=Google%20chrome\u0026logoColor=white\u0026labelColor=D35400' alt='Project Page'\u003e\u003c/a\u003e\n    \u003ca href=\"https://youtu.be/5PEd_p90kS0\"\u003e\u003cimg alt=\"youtube views\" title=\"Subscribe to my YouTube channel\" src=\"https://img.shields.io/youtube/views/5PEd_p90kS0?logo=youtube\u0026labelColor=ce4630\u0026style=for-the-badge\"/\u003e\u003c/a\u003e\n  \u003c/p\u003e\n\u003c/p\u003e\n\n\u003cbr/\u003e\n\nECON is designed for \"Human digitization from a color image\", which combines the best properties of implicit and explicit representations, to infer high-fidelity 3D clothed humans from in-the-wild images, even with **loose clothing** or in **challenging poses**. ECON also supports **multi-person reconstruction** and **SMPL-X based animation**.\n\u003cbr/\u003e\n\n\u003cdiv align=\"center\"\u003e\n\n|                                                                            **HuggingFace Demo**                                                                            |                                                                                             **Google Colab**                                                                                              |                                                                                                                                                                        **Blender Add-on**                                                                                                                                                                        |                                                             **Windows**                                                             |                                                                                **Docker**                                                                                 |\n| :------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------: |\n| \u003ca href=\"https://huggingface.co/spaces/Yuliang/ECON\"  style='padding-left: 0.5rem;'\u003e\u003cimg src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-ECON-orange'\u003e\u003c/a\u003e | \u003ca href='https://colab.research.google.com/drive/1YRgwoRCZIrSB2e7auEWFyG10Xzjbrbno?usp=sharing'\u003e\u003cimg src='https://img.shields.io/badge/Vanilla Colab-ec740b.svg?logo=googlecolab' alt='Google Colab'\u003e\u003c/a\u003e | \u003ca href='https://carlosedubarreto.gumroad.com/l/CEB_ECON'\u003e\u003cimg src='https://img.shields.io/badge/ECON-F6DDCC.svg?logo=Blender' alt='Blender'\u003e\u003c/a\u003e \u003ca href=\"https://youtu.be/sbWZbTf6ZYk\"\u003e\u003cimg alt=\"youtube views\" title=\"Subscribe to my YouTube channel\" src=\"https://img.shields.io/youtube/views/sbWZbTf6ZYk?logo=youtube\u0026labelColor=ce4630\u0026style=flat\"/\u003e\u003c/a\u003e | \u003ca href='./docs/installation-windows.md'\u003e\u003cimg src='https://img.shields.io/badge/Windows-0078D6.svg?logo=windows' alt='Windows'\u003e\u003c/a\u003e | \u003ca href='https://github.com/YuliangXiu/ECON/blob/master/docs/installation-docker.md'\u003e\u003cimg src='https://img.shields.io/badge/Docker-9cf.svg?logo=Docker' alt='Docker'\u003e\u003c/a\u003e |\n|                                                                                                                                                                            |                        \u003ca href='https://github.com/camenduru/ECON-colab'\u003e\u003cimg src='https://img.shields.io/badge/Gradio Colab-ec740b.svg?logo=googlecolab' alt='Google Colab'\u003e\u003c/a\u003e                         |  \u003ca href='https://github.com/kwan3854/CEB_ECON'\u003e\u003cimg src='https://img.shields.io/badge/ECON+TEXTure-F6DDCC.svg?logo=Blender' alt='Blender'\u003e\u003c/a\u003e \u003ca href=\"https://youtu.be/SDVfCeaI4AY\"\u003e\u003cimg alt=\"youtube views\" title=\"Subscribe to my YouTube channel\" src=\"https://img.shields.io/youtube/views/SDVfCeaI4AY?logo=youtube\u0026labelColor=ce4630\u0026style=flat\"/\u003e\u003c/a\u003e   |                                                                                                                                     |                                                                                                                                                                           |\n\n\u003c/div\u003e\n\n## Applications\n\n|                              ![SHHQ](assets/SHHQ.gif)                              |                                                ![crowd](assets/crowd.gif)                                                 |\n| :--------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------: |\n| \"3D guidance\" for [SHHQ Dataset](https://github.com/stylegan-human/StyleGAN-Human) |                                         multi-person reconstruction w/ occlusion                                          |\n|                        ![Blender](assets/blender-demo.gif)                         |                                            ![Animation](assets/animation.gif)                                             |\n|        \"All-in-One\" [Blender add-on](https://github.com/kwan3854/CEB_ECON)         | SMPL-X based Animation ([Instruction](https://github.com/YuliangXiu/ECON#animation-with-smpl-x-sequences-econ--hybrik-x)) |\n\n\u003cbr/\u003e\n\n## News :triangular_flag_on_post:\n\n- [2024/09/16] 🌟 Bending leg issues [[1](https://github.com/YuliangXiu/ECON/issues/133),[2](https://github.com/YuliangXiu/ECON/issues/5),[3](https://github.com/YuliangXiu/ICON/issues/68),[4](https://github.com/huangyangyi/TeCH/issues/14)] get resolved with [Sapiens](https://rawalkhirodkar.github.io/sapiens/), details in [Bending legs](https://github.com/YuliangXiu/ECON/blob/master/docs/tricks.md#bending-legs).\n- [2023/08/19] We released [TeCH](https://huangyangyi.github.io/TeCH/), which extends ECON with full texture support. \n- [2023/06/01] [Lee Kwan Joong](https://github.com/kwan3854) updates a Blender Addon ([Github](https://github.com/kwan3854/CEB_ECON), [Tutorial](https://youtu.be/SDVfCeaI4AY)).\n- [2023/04/16] \u003ca href=\"https://huggingface.co/spaces/Yuliang/ECON\"  style='padding-left: 0.5rem;'\u003e\u003cimg src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-orange'\u003e\u003c/a\u003e is ready to use!\n- [2023/02/27] ECON got accepted by CVPR 2023 as Highlight (top 10%)!\n- [2023/01/12] [Carlos Barreto](https://twitter.com/carlosedubarret/status/1613252471035494403) creates a Blender Addon ([Download](https://carlosedubarreto.gumroad.com/l/CEB_ECON), [Tutorial](https://youtu.be/sbWZbTf6ZYk)).\n- [2023/01/08] [Teddy Huang](https://github.com/Teddy12155555) creates [install-with-docker](docs/installation-docker.md) for ECON .\n- [2023/01/06] [Justin John](https://github.com/justinjohn0306) and [Carlos Barreto](https://github.com/carlosedubarreto) creates [install-on-windows](docs/installation-windows.md) for ECON .\n- [2022/12/22] \u003ca href='https://colab.research.google.com/drive/1YRgwoRCZIrSB2e7auEWFyG10Xzjbrbno?usp=sharing' style='padding-left: 0.5rem;'\u003e\u003cimg src='https://colab.research.google.com/assets/colab-badge.svg' alt='Google Colab'\u003e\u003c/a\u003e is now available, created by [Aron Arzoomand](https://github.com/AroArz).\n- [2022/12/15] Both \u003ca href=\"#demo\"\u003edemo\u003c/a\u003e and \u003ca href=\"https://arxiv.org/abs/2212.07422\"\u003earXiv\u003c/a\u003e are available.\n\n## Key idea: d-BiNI\n\nd-BiNI jointly optimizes front-back 2.5D surfaces such that: (1) high-frequency surface details agree with normal maps, (2) low-frequency surface variations, including discontinuities, align with SMPL-X surfaces, and (3) front-back 2.5D surface silhouettes are coherent with each other.\n\n|        Front-view        |        Back-view        |         Side-view         |\n| :----------------------: | :---------------------: | :-----------------------: |\n| ![](assets/front-45.gif) | ![](assets/back-45.gif) | ![](assets/double-90.gif) |\n\n\u003cdetails\u003e\u003csummary\u003ePlease consider cite \u003cstrong\u003eBiNI\u003c/strong\u003e if it also helps on your project\u003c/summary\u003e\n\n```bibtex\n@inproceedings{cao2022bilateral,\n  title={Bilateral normal integration},\n  author={Cao, Xu and Santo, Hiroaki and Shi, Boxin and Okura, Fumio and Matsushita, Yasuyuki},\n  booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part I},\n  pages={552--567},\n  year={2022},\n  organization={Springer}\n}\n```\n\n\u003c/details\u003e\n\n\u003cbr\u003e\n\n\u003c!-- TABLE OF CONTENTS --\u003e\n\u003cdetails open=\"open\" style='padding: 10px; border-radius:5px 30px 30px 5px; border-style: solid; border-width: 1px;'\u003e\n  \u003csummary\u003eTable of Contents\u003c/summary\u003e\n  \u003col\u003e\n    \u003cli\u003e\n      \u003ca href=\"#instructions\"\u003eInstructions\u003c/a\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\n      \u003ca href=\"#demos\"\u003eDemos\u003c/a\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\n      \u003ca href=\"#citation\"\u003eCitation\u003c/a\u003e\n    \u003c/li\u003e\n  \u003c/ol\u003e\n\u003c/details\u003e\n\u003cbr/\u003e\n\n## Instructions\n\n- See [installion doc for Docker](docs/installation-docker.md) to run a docker container with pre-built image for ECON demo\n- See [installion doc for Windows](docs/installation-windows.md) to install all the required packages and setup the models on _Windows_\n- See [installion doc for Ubuntu](docs/installation-ubuntu.md) to install all the required packages and setup the models on _Ubuntu_\n- See [magic tricks](docs/tricks.md) to know a few technical tricks to further improve and accelerate ECON\n- See [testing](docs/testing.md) to prepare the testing data and evaluate ECON\n\n## Demos\n\n- ### Quick Start\n\n```bash\n# For single-person image-based reconstruction (w/ l visualization steps, 1.8min)\npython -m apps.infer -cfg ./configs/econ.yaml -in_dir ./examples -out_dir ./results\n\n# For multi-person image-based reconstruction (see config/econ.yaml)\npython -m apps.infer -cfg ./configs/econ.yaml -in_dir ./examples -out_dir ./results -multi\n\n# To generate the demo video of reconstruction results\npython -m apps.multi_render -n \u003cfile_name\u003e\n\n```\n\n- ### Animation with SMPL-X sequences (ECON + [HybrIK-X](https://github.com/Jeff-sjtu/HybrIK#smpl-x))\n\n```bash\n# 1. Use HybrIK-X to estimate SMPL-X pose sequences from input video\n# 2. Rig ECON's reconstruction mesh, to be compatible with SMPL-X's parametrization (-dress for dress/skirts).\n# 3. Animate with SMPL-X pose sequences obtained from HybrIK-X, getting \u003cfile_name\u003e_motion.npz\n# 4. Render the frames with Blender (rgb-partial texture, normal-normal colors), and combine them to get final video\n\npython -m apps.avatarizer -n \u003cfile_name\u003e\npython -m apps.animation -n \u003cfile_name\u003e -m \u003cmotion_name\u003e\n\n# Note: to install missing python packages into Blender\n# blender -b --python-expr \"__import__('pip._internal')._internal.main(['install', 'moviepy'])\"\n\nwget https://download.is.tue.mpg.de/icon/econ_empty.blend\nblender -b --python apps.blender_dance.py -- normal \u003cfile_name\u003e 10 \u003e /tmp/NULL\n```\n\n\u003cdetails\u003e\u003csummary\u003ePlease consider cite \u003cstrong\u003eHybrIK-X\u003c/strong\u003e if it also helps on your project\u003c/summary\u003e\n\n```bibtex\n@article{li2023hybrik,\n  title={HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-body Mesh Recovery},\n  author={Li, Jiefeng and Bian, Siyuan and Xu, Chao and Chen, Zhicun and Yang, Lixin and Lu, Cewu},\n  journal={arXiv preprint arXiv:2304.05690},\n  year={2023}\n}\n```\n\n\u003c/details\u003e\n\n- ### Gradio Demo\n\nWe also provide a UI for testing our method that is built with gradio. This demo also supports pose\u0026prompt guided human image generation! Running the following command in a terminal will launch the demo:\n\n```bash\ngit checkout main\npython app.py\n```\n\nThis demo is also hosted on HuggingFace Space \u003ca href=\"https://huggingface.co/spaces/Yuliang/ECON\"  style='padding-left: 0.5rem;'\u003e\u003cimg src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-ECON-orange'\u003e\u003c/a\u003e\n\n- ### Full Texture Generation\n\n#### Method 1: ECON+TEXTure\n\nPlease firstly follow the [TEXTure's installation](https://github.com/YuliangXiu/TEXTure#installation-floppy_disk) to setup the env of TEXTure.\n\n```bash\n\n# generate required UV atlas\npython -m apps.avatarizer -n \u003cfile_name\u003e -uv\n\n# generate new texture using TEXTure\ngit clone https://github.com/YuliangXiu/TEXTure\ncd TEXTure\nln -s ../ECON/results/econ/cache\npython -m scripts.run_texture --config_path=configs/text_guided/avatar.yaml\n```\n\nThen check `./experiments/\u003cfile_name\u003e/mesh` for the results.\n\n\u003cdetails\u003e\u003csummary\u003ePlease consider cite \u003cstrong\u003eTEXTure\u003c/strong\u003e if it also helps on your project\u003c/summary\u003e\n\n```bibtex\n@article{richardson2023texture,\n  title={Texture: Text-guided texturing of 3d shapes},\n  author={Richardson, Elad and Metzer, Gal and Alaluf, Yuval and Giryes, Raja and Cohen-Or, Daniel},\n  journal={ACM Transactions on Graphics (TOG)},\n  publisher={ACM New York, NY, USA},\n  year={2023}\n}\n```\n\u003c/details\u003e\n\n#### Method 2: TeCH\n\nPlease check out our new paper, *TeCH: Text-guided Reconstruction of Lifelike Clothed Humans* ([Page](https://huangyangyi.github.io/TeCH/), [Code](https://github.com/huangyangyi/TeCH))\n\n\u003cdetails\u003e\u003csummary\u003ePlease consider cite \u003cstrong\u003eTeCH\u003c/strong\u003e if it also helps on your project\u003c/summary\u003e\n\n```bibtex\n@inproceedings{huang2024tech,\n  title={{TeCH: Text-guided Reconstruction of Lifelike Clothed Humans}},\n  author={Huang, Yangyi and Yi, Hongwei and Xiu, Yuliang and Liao, Tingting and Tang, Jiaxiang and Cai, Deng and Thies, Justus},\n  booktitle={International Conference on 3D Vision (3DV)},\n  year={2024}\n}\n```\n\n\u003c/details\u003e\n\n\u003cbr/\u003e\n\n## More Qualitative Results\n\n|   ![OOD Poses](assets/OOD-poses.jpg)   |\n| :------------------------------------: |\n|          _Challenging Poses_           |\n| ![OOD Clothes](assets/OOD-outfits.jpg) |\n|            _Loose Clothes_             |\n\n\u003cbr/\u003e\n\u003cbr/\u003e\n\n## Citation\n\n```bibtex\n@inproceedings{xiu2023econ,\n  title     = {{ECON: Explicit Clothed humans Optimized via Normal integration}},\n  author    = {Xiu, Yuliang and Yang, Jinlong and Cao, Xu and Tzionas, Dimitrios and Black, Michael J.},\n  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},\n  month     = {June},\n  year      = {2023},\n}\n```\n\n\u003cbr/\u003e\n\n## Acknowledgments\n\nWe thank [Lea Hering](https://is.mpg.de/person/lhering) and [Radek Daněček](https://is.mpg.de/person/rdanecek) for proof reading, [Yao Feng](https://ps.is.mpg.de/person/yfeng), [Haven Feng](https://is.mpg.de/person/hfeng), and [Weiyang Liu](https://wyliu.com/) for their feedback and discussions, [Tsvetelina Alexiadis](https://ps.is.mpg.de/person/talexiadis) for her help with the AMT perceptual study.\n\nHere are some great resources we benefit from:\n\n- [ICON](https://github.com/YuliangXiu/ICON) for SMPL-X Body Fitting\n- [BiNI](https://github.com/hoshino042/bilateral_normal_integration) for Bilateral Normal Integration\n- [MonoPortDataset](https://github.com/Project-Splinter/MonoPortDataset) for Data Processing, [MonoPort](https://github.com/Project-Splinter/MonoPort) for fast implicit surface query\n- [rembg](https://github.com/danielgatis/rembg) for Human Segmentation\n- [Sapiens](https://rawalkhirodkar.github.io/sapiens/) for normal estimation\n- [MediaPipe](https://google.github.io/mediapipe/getting_started/python.html) for full-body landmark estimation\n- [PyTorch-NICP](https://github.com/wuhaozhe/pytorch-nicp) for non-rigid registration\n- [smplx](https://github.com/vchoutas/smplx), [PyMAF-X](https://www.liuyebin.com/pymaf-x/), [PIXIE](https://github.com/YadiraF/PIXIE) for Human Pose \u0026 Shape Estimation\n- [CAPE](https://github.com/qianlim/CAPE) and [THuman](https://github.com/ZhengZerong/DeepHuman/tree/master/THUmanDataset) for Dataset\n- [PyTorch3D](https://github.com/facebookresearch/pytorch3d) for Differential Rendering\n\nSome images used in the qualitative examples come from [pinterest.com](https://www.pinterest.com/).\n\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No.860768 ([CLIPE Project](https://www.clipe-itn.eu)).\n\n## Contributors\n\nKudos to all of our amazing contributors! ECON thrives through open-source. In that spirit, we welcome all kinds of contributions from the community.\n\n\u003ca href=\"https://github.com/yuliangxiu/ECON/graphs/contributors\"\u003e\n  \u003cimg src=\"https://contrib.rocks/image?repo=yuliangxiu/ECON\" /\u003e\n\u003c/a\u003e\n\n_Contributor avatars are randomly shuffled._\n\n---\n\n\u003cbr\u003e\n\n## License\n\nThis code and model are available for non-commercial scientific research purposes as defined in the [LICENSE](LICENSE) file. By downloading and using the code and model you agree to the terms in the [LICENSE](LICENSE).\n\n## Disclosure\n\nMJB has received research gift funds from Adobe, Intel, Nvidia, Meta/Facebook, and Amazon. MJB has financial interests in Amazon, Datagen Technologies, and Meshcapade GmbH. While MJB is a part-time employee of Meshcapade, his research was performed solely at, and funded solely by, the Max Planck Society.\n\n## Contact\n\nFor technical questions, please contact yuliang.xiu@tue.mpg.de\n\nFor commercial licensing, please contact ps-licensing@tue.mpg.de\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FYuliangXiu%2FECON","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FYuliangXiu%2FECON","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FYuliangXiu%2FECON/lists"}