[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-72151":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":34,"readmeContent":35,"aiSummary":36,"trendingCount":16,"starSnapshotCount":16,"syncStatus":37,"lastSyncTime":38,"discoverSource":39},72151,"echomimic_v2","antgroup\u002Fechomimic_v2","antgroup","[CVPR 2025] EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation","https:\u002F\u002Fantgroup.github.io\u002Fai\u002Fechomimic_v2\u002F",null,"Python",4583,539,47,74,0,6,8,19,18,30.2,"Apache License 2.0",false,"main",[26,27,28,29,30,31,32,33],"audio-driven-body-animation","audio-driven-portrait-animations","audio-driven-talking-face","cvpr2025","human-animation","talking-face-generation","talking-head","video-generation","2026-06-12 02:02:59","\u003Ch1 align='center'>EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation\u003C\u002Fh1>\r\n\r\n\u003Cdiv align='center'>\r\n    \u003Ca href='https:\u002F\u002Fgithub.com\u002Fmengrang' target='_blank'>Rang Meng\u003C\u002Fa>\u003Csup>1\u003C\u002Fsup> \r\n    \u003Ca href='https:\u002F\u002Fgithub.com\u002F' target='_blank'>Xingyu Zhang\u003C\u002Fa> \r\n    \u003Ca href='https:\u002F\u002Flymhust.github.io\u002F' target='_blank'>Yuming Li\u003C\u002Fa>\u003Csup>2\u003C\u002Fsup> \r\n    \u003Ca href='https:\u002F\u002Fopenreview.net\u002Fprofile?id=~Chenguang_Ma3' target='_blank'>Chenguang Ma\u003C\u002Fa>\u003Csup>2\u003C\u002Fsup>\r\n\u003C\u002Fdiv>\r\n\r\n\u003Cdiv align='center'>\r\nTerminal Technology Department, Alipay, Ant Group.\r\n\u003C\u002Fdiv>\r\n\r\n\u003Cp align='center'>\r\n    \u003Csup>1\u003C\u002Fsup>Core Contributor \r\n    \u003Csup>2\u003C\u002Fsup>Corresponding Authors\r\n\u003C\u002Fp>\r\n\u003Cdiv align='center'>\r\n    \u003Ca href='https:\u002F\u002Fantgroup.github.io\u002Fai\u002Fechomimic_v2\u002F'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FProject-Page-blue'>\u003C\u002Fa>\r\n    \u003Ca href='https:\u002F\u002Fhuggingface.co\u002FBadToBest\u002FEchoMimicV2'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%A4%97%20HuggingFace-Model-yellow'>\u003C\u002Fa>\r\n    \u003C!--\u003Ca href='https:\u002F\u002Fantgroup.github.io\u002Fai\u002Fechomimic_v2\u002F'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%A4%97%20HuggingFace-Demo-yellow'>\u003C\u002Fa>-->\r\n    \u003Ca href='https:\u002F\u002Fmodelscope.cn\u002Fmodels\u002FBadToBest\u002FEchoMimicV2'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FModelScope-Model-purple'>\u003C\u002Fa>\r\n    \u003C!--\u003Ca href='https:\u002F\u002Fantgroup.github.io\u002Fai\u002Fechomimic_v2\u002F'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FModelScope-Demo-purple'>\u003C\u002Fa>-->\r\n    \u003Ca href='https:\u002F\u002Farxiv.org\u002Fabs\u002F2411.10061'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPaper-Arxiv-red'>\u003C\u002Fa>\r\n    \u003Ca href='https:\u002F\u002Fopenaccess.thecvf.com\u002Fcontent\u002FCVPR2025\u002Fpapers\u002FMeng_EchoMimicV2_Towards_Striking_Simplified_and_Semi-Body_Human_Animation_CVPR_2025_paper.pdf'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPaper-CVPR2025-blue'>\u003C\u002Fa>\r\n    \u003Ca href='https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fblob\u002Fmain\u002Fassets\u002Fhalfbody_demo\u002Fwechat_group.png'>\u003Cimg src='https:\u002F\u002Fbadges.aleen42.com\u002Fsrc\u002Fwechat.svg'>\u003C\u002Fa>\r\n\u003C\u002Fdiv>\r\n\u003Cdiv align='center'>\r\n    \u003Ca href='https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fdiscussions\u002F53'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEnglish-Common Problems-orange'>\u003C\u002Fa>\r\n    \u003Ca href='https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fdiscussions\u002F40'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F中文版-常见问题汇总-orange'>\u003C\u002Fa>\r\n\u003C\u002Fdiv>\r\n\r\n## 🚀 EchoMimic Series\r\n* EchoMimicV1: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditioning. [GitHub](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic)\r\n* EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation. [GitHub](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2)\r\n* EchoMimicV3: 1.3B Parameters are All You Need for Unified Multi-Modal and Multi-Task Human Animation. [GitHub](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v3)\r\n\r\n## 📣 Updates\r\n* [2025.08.09] 🔥🔥 We update the EchoMimicV3 and release the code.\r\n* [2025.02.27] 🔥 EchoMimicV2 is accepted by CVPR 2025.\r\n* [2025.01.16] 🔥 Please check out the [discussions](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fdiscussions) to learn how to start EchoMimicV2.\r\n* [2025.01.16] 🚀🔥 [GradioUI for Accelerated EchoMimicV2](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fblob\u002Fmain\u002Fapp_acc.py) is now available.\r\n* [2025.01.03] 🚀🔥 **One Minute is All You Need to Generate Video**. [Accelerated EchoMimicV2](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fblob\u002Fmain\u002Finfer_acc.py) are released. The inference speed can be improved by 9x (from ~7mins\u002F120frames to ~50s\u002F120frames on A100 GPU).\r\n* [2024.12.16] 🔥 [RefImg-Pose Alignment Demo](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fblob\u002Fmain\u002Fdemo.ipynb) is now available, which involves aligning reference image, extracting pose from driving video, and generating video.\r\n* [2024.11.27] 🔥 [Installation tutorial](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=2ab6U1-nVTQ) is now available. Thanks [AiMotionStudio](https:\u002F\u002Fwww.youtube.com\u002F@AiMotionStudio) for the contribution.\r\n* [2024.11.22] 🔥 [GradioUI](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fblob\u002Fmain\u002Fapp.py) is now available. Thanks @gluttony-10 for the contribution.\r\n* [2024.11.22] 🔥 [ComfyUI](https:\u002F\u002Fgithub.com\u002Fsmthemex\u002FComfyUI_EchoMimic) is now available. Thanks @smthemex for the contribution.\r\n* [2024.11.21] 🔥 We release the EMTD dataset list and processing scripts.\r\n* [2024.11.21] 🔥 We release our [EchoMimicV2](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2) codes and models.\r\n* [2024.11.15] 🔥 Our [paper](https:\u002F\u002Farxiv.org\u002Fabs\u002F2411.10061) is in public on arxiv.\r\n\r\n## 🌅 Gallery\r\n### Introduction\r\n\u003Ctable class=\"center\">\r\n\u003Ctr>\r\n    \u003Ctd width=50% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Ff544dfc0-7d1a-4c2c-83c0-608f28ffda25\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=50% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F7f626b65-725c-4158-a96b-062539874c63\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003C\u002Ftable>\r\n\r\n### English Driven Audio\r\n\u003Ctable class=\"center\">\r\n\u003Ctr>\r\n    \u003Ctd width=100% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F3d5ac52c-62e4-41bc-8b27-96f005bbd781\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003C\u002Ftable>\r\n\u003Ctable class=\"center\">\r\n\u003Ctr>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fe8dd6919-665e-4343-931f-54c93dc49a7d\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F2a377391-a0d3-4a9d-8dde-cc59006e7e5b\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F462bf3bb-0af2-43e2-a2dc-559e79953f3c\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003Ctr>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F0e988e7f-6346-4b54-9061-9cfc7a80e9c8\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F56f739bd-afbf-4ed3-ab15-73a811c1bc46\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F1b2f7827-111d-4fc0-a773-e1731bba285d\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003Ctr>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fa76b6cc8-89b9-4f7e-b1ce-c85a657b6dc7\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fbf03b407-5033-4a30-aa59-b8680a515181\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Ff98b3985-572c-499f-ae1a-1b9befe3086f\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003C\u002Ftable>\r\n\r\n### Chinese Driven Audio\r\n\u003Ctable class=\"center\">\r\n\u003Ctr>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fa940a332-2fd1-48e7-b3c4-f88f63fd1c9d\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F8f185829-c67f-45f4-846c-fcbe012c3acf\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fa49ab9be-f17b-41c5-96dd-20dc8d759b45\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003Ctr>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F1136ec68-a13c-4ee7-ab31-5621530bf9df\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Ffc16d512-8806-4662-ae07-8fcf45c75a83\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Ff8559cd1-f555-4781-9251-dfcef10b5b01\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003Ctr>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fc7473e3a-ab51-4ad5-be96-6c4691fc0c6e\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fca69eac0-5126-41ee-8cac-c9722004d771\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n    \u003Ctd width=30% style=\"border: none\">\r\n        \u003Cvideo controls loop src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fe66f1712-b66d-46b5-8bbd-811fbcfea4fd\" muted=\"false\">\u003C\u002Fvideo>\r\n    \u003C\u002Ftd>\r\n\u003C\u002Ftr>\r\n\u003C\u002Ftable>\r\n\r\n## ⚒️ Automatic Installation\r\n### Download the Codes\r\n\r\n```bash\r\n  git clone https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\r\n  cd echomimic_v2\r\n```\r\n### Automatic Setup\r\n- CUDA >= 11.7, Python == 3.10\r\n\r\n```bash\r\n   sh linux_setup.sh\r\n```\r\n## ⚒️ Manual Installation\r\n### Download the Codes\r\n\r\n```bash\r\n  git clone https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\r\n  cd echomimic_v2\r\n```\r\n### Python Environment Setup\r\n\r\n- Tested System Environment: Centos 7.2\u002FUbuntu 22.04, Cuda >= 11.7\r\n- Tested GPUs: A100(80G) \u002F RTX4090D (24G) \u002F V100(16G)\r\n- Tested Python Version: 3.8 \u002F 3.10 \u002F 3.11\r\n\r\nCreate conda environment (Recommended):\r\n\r\n```bash\r\n  conda create -n echomimic python=3.10\r\n  conda activate echomimic\r\n```\r\n\r\nInstall packages with `pip`\r\n```bash\r\n  pip install pip -U\r\n  pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 xformers==0.0.28.post3 --index-url https:\u002F\u002Fdownload.pytorch.org\u002Fwhl\u002Fcu124\r\n  pip install torchao --index-url https:\u002F\u002Fdownload.pytorch.org\u002Fwhl\u002Fnightly\u002Fcu124\r\n  pip install -r requirements.txt\r\n  pip install --no-deps facenet_pytorch==2.6.0\r\n```\r\n\r\n### Download ffmpeg-static\r\nDownload and decompress [ffmpeg-static](https:\u002F\u002Fwww.johnvansickle.com\u002Fffmpeg\u002Fold-releases\u002Fffmpeg-4.4-amd64-static.tar.xz), then\r\n```\r\nexport FFMPEG_PATH=\u002Fpath\u002Fto\u002Fffmpeg-4.4-amd64-static\r\n```\r\n\r\n### Download pretrained weights\r\n\r\n```shell\r\ngit lfs install\r\ngit clone https:\u002F\u002Fhuggingface.co\u002FBadToBest\u002FEchoMimicV2 pretrained_weights\r\n```\r\n\r\nThe **pretrained_weights** is organized as follows.\r\n\r\n```\r\n.\u002Fpretrained_weights\u002F\r\n├── denoising_unet.pth\r\n├── reference_unet.pth\r\n├── motion_module.pth\r\n├── pose_encoder.pth\r\n├── sd-vae-ft-mse\r\n│   └── ...\r\n└── audio_processor\r\n    └── tiny.pt\r\n```\r\n\r\nIn which **denoising_unet.pth** \u002F **reference_unet.pth** \u002F **motion_module.pth** \u002F **pose_encoder.pth** are the main checkpoints of **EchoMimic**. Other models in this hub can be also downloaded from it's original hub, thanks to their brilliant works:\r\n- [sd-vae-ft-mse](https:\u002F\u002Fhuggingface.co\u002Fstabilityai\u002Fsd-vae-ft-mse)\r\n- [audio_processor(whisper)](https:\u002F\u002Fopenaipublic.azureedge.net\u002Fmain\u002Fwhisper\u002Fmodels\u002F65147644a518d12f04e32d6f3b26facc3f8dd46e5390956a9424a650c0ce22b9\u002Ftiny.pt)\r\n\r\n### Inference on Demo \r\nRun the gradio:\r\n```bash\r\npython app.py\r\n```\r\nRun the python inference script:\r\n```bash\r\npython infer.py --config='.\u002Fconfigs\u002Fprompts\u002Finfer.yaml'\r\n```\r\n\r\nRun the python inference script for accelerated version. Make sure to check out the configuration for accelerated inference:\r\n```bash\r\npython infer_acc.py --config='.\u002Fconfigs\u002Fprompts\u002Finfer_acc.yaml'\r\n```\r\n\r\n### EMTD Dataset\r\nDownload dataset:\r\n```bash\r\npython .\u002FEMTD_dataset\u002Fdownload.py\r\n```\r\nSlice dataset:\r\n```bash\r\nbash .\u002FEMTD_dataset\u002Fslice.sh\r\n```\r\nProcess dataset:\r\n```bash\r\npython .\u002FEMTD_dataset\u002Fpreprocess.py\r\n```\r\nMake sure to check out the [discussions](https:\u002F\u002Fgithub.com\u002Fantgroup\u002Fechomimic_v2\u002Fdiscussions) to learn how to start the inference.\r\n\r\n## 📝 Release Plans\r\n\r\n|  Status  | Milestone                                                                | ETA |\r\n|:--------:|:-------------------------------------------------------------------------|:--:|\r\n|    ✅    | The inference source code of EchoMimicV2 meet everyone on GitHub   | 21st Nov, 2024 |\r\n|    ✅    | Pretrained models trained on English and Mandarin Chinese on HuggingFace | 21st Nov, 2024 |\r\n|    ✅    | Pretrained models trained on English and Mandarin Chinese on ModelScope   | 21st Nov, 2024 |\r\n|    ✅    | EMTD dataset list and processing scripts                | 21st Nov, 2024 |\r\n|    ✅    | Jupyter demo with pose and reference image alignmnet                | 16st Dec, 2024 |\r\n|    ✅    | Accelerated models                                        | 3st Jan, 2025 |\r\n|    🚀    | Online Demo on ModelScope to be released            | TBD |\r\n|    🚀    | Online Demo on HuggingFace to be released         | TBD |\r\n\r\n## ⚖️ Disclaimer\r\nThis project is intended for academic research, and we explicitly disclaim any responsibility for user-generated content. Users are solely liable for their actions while using the generative model. The project contributors have no legal affiliation with, nor accountability for, users' behaviors. It is imperative to use the generative model responsibly, adhering to both ethical and legal standards.\r\n\r\n## 🙏🏻 Acknowledgements\r\n\r\nWe would like to thank the contributors to the [MimicMotion](https:\u002F\u002Fgithub.com\u002FTencent\u002FMimicMotion) and [Moore-AnimateAnyone](https:\u002F\u002Fgithub.com\u002FMooreThreads\u002FMoore-AnimateAnyone) repositories, for their open research and exploration. \r\n\r\nWe are also grateful to [CyberHost](https:\u002F\u002Fcyberhost.github.io\u002F) and [Vlogger](https:\u002F\u002Fenriccorona.github.io\u002Fvlogger\u002F) for their outstanding work in the area of audio-driven human animation.\r\n\r\nIf we missed any open-source projects or related articles, we would like to complement the acknowledgement of this specific work immediately.\r\n\r\n## 📒 Citation\r\n\r\nIf you find our work useful for your research, please consider citing the paper :\r\n\r\n```\r\n@article{meng2024echomimicv2,\r\n  title={EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation},\r\n  author={Meng, Rang and Zhang, Xingyu and Li, Yuming and Ma, Chenguang},\r\n  journal={arXiv preprint arXiv:2411.10061},\r\n  year={2024}\r\n}\r\n@article{meng2025echomimicv3,\r\n  title={Echomimicv3: 1.3 b parameters are all you need for unified multi-modal and multi-task human animation},\r\n  author={Meng, Rang and Wang, Yan and Wu, Weipeng and Zheng, Ruobing and Li, Yuming and Ma, Chenguang},\r\n  journal={arXiv preprint arXiv:2507.03905},\r\n  year={2025}\r\n}\r\n@article{meng2026echotorrent,\r\n  title={EchoTorrent: Towards Swift, Sustained, and Streaming Multi-Modal Video Generation},\r\n  author={Meng, Rang and Wu, Weipeng and Yin, Yingjie and Li, Yuming and Ma, Chenguang},\r\n  journal={arXiv preprint arXiv:2602.13669},\r\n  year={2026}\r\n}\r\n```\r\n\r\n## 🌟 Star History\r\n[![Star History Chart](https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=antgroup\u002Fechomimic_v2&type=Date)](https:\u002F\u002Fstar-history.com\u002F#antgroup\u002Fechomimic_v2&Date)\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n","EchoMimicV2 是一个音频驱动的半身人体动画生成项目。该项目利用先进的深度学习技术，能够根据输入的音频生成高质量、自然流畅的人体上半身动画，支持面部表情和头部动作的同步。其核心技术特点包括简化的工作流程、高效的模型架构以及对多种音频输入的良好适应性。适合应用于虚拟主播、在线教育、游戏角色动画制作等场景，为用户提供更加生动逼真的交互体验。项目采用 Python 编写，遵循 Apache License 2.0 开源协议，并已在 CVPR 2025 上发表相关论文。",2,"2026-06-11 03:40:35","high_star"]