base on GeneFace++: Generalized and Stable Real-Time 3D Talking Face Generation; Official Code # GeneFace++: Generalized and Stable Real-Time 3D Talking Face Generation [](https://arxiv.org/abs/2305.00787)| [](https://github.com/yerfor/GeneFacePlusPlus) | [中文文档](./README-zh.md) This is the official implementation of GeneFace++ [Paper](https://arxiv.org/abs/2301.13430) with Pytorch, which enables high lip-sync, high video-reality and high system-efficiency 3D talking face generation. You can visit our [Demo Page](https://genefaceplusplus.github.io/) to watch demo videos and learn more details. <p align="center"> <br> <img src="assets/geneface++.png" width="100%"/> <br> </p> # 🔥MimicTalk Released **We have released the code of MimicTalk ([https://github.com/yerfor/MimicTalk/](https://github.com/yerfor/MimicTalk/)), which is a SOTA NeRF-based person-specific talking face method and achieves better visual quality and enables talking style control.** ## You may also interested in - We release Real3D-portrait (ICLR 2024 Spotlight), ([https://github.com/yerfor/Real3DPortrait](https://github.com/yerfor/Real3DPortrait)), a NeRF-based one-shot talking face system. Only upload one image and enjoy realistic talking face! ## Quick Start! We provide a guide for a quick start in GeneFace++. - Step 1: Follow the steps in `docs/prepare_env/install_guide.md`, create a new python environment named `geneface`, and download 3DMM files into `deep_3drecib/BFM`. - Step 2: Download pre-processed dataset of May([Google Drive](https://drive.google.com/drive/folders/1SwZ7uRa5ESzzq_Cd21-Lk5heAZxa9oZO?usp=sharing) or [BaiduYun Disk](https://pan.baidu.com/s/1U_FalVoxgb9sAb9FD1cZEw?pwd=98n4) with password 98n4), and place it here `data/binary/videos/May/trainval_dataset.npy` - Step 3: Download pre-trained audio-to-motino model `audio2motion_vae.zip` ([Google Drive](https://drive.google.com/drive/folders/1M6CQH52lG_yZj7oCMaepn3Qsvb-8W2pT?usp=sharing) or [BaiduYun Disk](https://pan.baidu.com/s/19UZxMrO-ZvkOeYzUkOKsTQ?pwd=9cqp) with password 9cqp) and motion-to-video checkpoint `motion2video_nerf.zip`, which is specific to May (in this [Google Drive](https://drive.google.com/drive/folders/1M6CQH52lG_yZj7oCMaepn3Qsvb-8W2pT?usp=sharing) or in this[BaiduYun Disk](https://pan.baidu.com/s/1U_FalVoxgb9sAb9FD1cZEw?pwd=98n4) with password 98n4), and unzip them to `./checkpoints/` After these steps，your directories `checkpoints` and `data` should be like this： ``` > checkpoints > audio2motion_vae > motion2video_nerf > may_head > may_torso > data > binary > videos > May trainval_dataset.npy ``` - Step 4: activate `geneface` Python environment, and execute: ```bash export PYTHONPATH=./ python inference/genefacepp_infer.py --a2m_ckpt=checkpoints/audio2motion_vae --head_ckpt= --torso_ckpt=checkpoints/motion2video_nerf/may_torso --drv_aud=data/raw/val_wavs/MacronSpeech.wav --out_name=may_demo.mp4 ``` Or you can play with our Gradio WebUI: ```bash export PYTHONPATH=./ python inference/app_genefacepp.py --a2m_ckpt=checkpoints/audio2motion_vae --head_ckpt= --torso_ckpt=checkpoints/motion2video_nerf/may_torso ``` Or use our provided [Google Colab](https://colab.research.google.com/github/yerfor/GeneFacePlusPlus/blob/main/inference/genefacepp_demo.ipynb) and run all cells in it. ## Train GeneFace++ with your own videos Please refer to details in `docs/process_data` and `docs/train_and_infer`. Below are answers to frequently asked questions when training GeneFace++ on custom videos: - Please make sure that the head segment occupies a relatively large region in the video (e.g., similar to the provided `May.mp4`). Or you need to hand-crop your training video. [issue](https://github.com/yerfor/GeneFacePlusPlus/issues/30) - Make sure that the talking person appears in every frame of the video, otherwise the data preprocessing pipeline may be failed. - We only tested our code on Liunx (Ubuntu/CentOS). It is welcome that someone who are willing to share their installation guide on Windows/MacOS. ## ToDo - [x] **Release Inference Code of Audio2Motion and Motion2Video.** - [x] **Release Pre-trained weights of Audio2Motion and Motion2Video.** - [x] **Release Training Code of Motino2Video Renderer.** - [x] **Release Gradio Demo.** - [x] **Release Google Colab.** - [ ] **Release Training Code of Audio2Motion and Post-Net. (Maybe 2024.06.01) ** ## Citation If you found this repo helpful to your work, please consider cite us: ``` @article{ye2023geneface, title={GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis}, author={Ye, Zhenhui and Jiang, Ziyue and Ren, Yi and Liu, Jinglin and He, Jinzheng and Zhao, Zhou}, journal={arXiv preprint arXiv:2301.13430}, year={2023} } @article{ye2023geneface++, title={GeneFace++: Generalized and Stable Real-Time Audio-Driven 3D Talking Face Generation}, author={Ye, Zhenhui and He, Jinzheng and Jiang, Ziyue and Huang, Rongjie and Huang, Jiawei and Liu, Jinglin and Ren, Yi and Yin, Xiang and Ma, Zejun and Zhao, Zhou}, journal={arXiv preprint arXiv:2305.00787}, year={2023} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"8174","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"