Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis | ICLR 2024 Spotlight
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这个仓库是Real3D-Portrait的官方PyTorch实现, 用于实现单参考图(one-shot)、高视频真实度(video reality)的虚拟人视频合成。您可以访问我们的项目页面以观看Demo视频, 阅读我们的论文以了解技术细节。
您可能同样感兴趣
- 我们发布了GeneFace++(https://github.com/yerfor/GeneFacePlusPlus), 一个专注于提升单个特定说话人效果的说话人合成系统,它实现了高嘴形对齐、高视频质量和高系统效率。
快速上手!
安装环境
请参照环境配置文档,配置Conda环境real3dportrait
下载预训练与第三方模型
3DMM BFM模型
下载3DMM BFM模型:Google Drive 或 BaiduYun Disk 提取码: m9q5
下载完成后,放置全部的文件到deep_3drecon/BFM
里,文件结构如下:
deep_3drecon/BFM/
├── 01_MorphableModel.mat
├── BFM_exp_idx.mat
├── BFM_front_idx.mat
├── BFM_model_front.mat
├── Exp_Pca.bin
├── facemodel_info.mat
├── index_mp468_from_mesh35709.npy
├── mediapipe_in_bfm53201.npy
└── std_exp.txt
预训练模型
下载预训练的Real3D-Portrait:Google Drive 或 BaiduYun Disk 提取码: 6x4f
下载完成后,放置全部的文件到checkpoints
里并解压,文件结构如下:
checkpoints/
├── 240210_real3dportrait_orig
│ ├── audio2secc_vae
│ │ ├── config.yaml
│ │ └── model_ckpt_steps_400000.ckpt
│ └── secc2plane_torso_orig
│ ├── config.yaml
│ └── model_ckpt_steps_100000.ckpt
└── pretrained_ckpts
└── mit_b0.pth
推理测试
我们目前提供了命令行(CLI), Gradio WebUI与Google Colab推理方式。我们同时支持音频驱动(Audio-Driven)与视频驱动(Video-Driven):
- 音频驱动场景下,需要至少提供
source image
与driving audio
- 视频驱动场景下,需要至少提供
source image
与driving expression video
Gradio WebUI推理
启动Gradio WebUI,按照提示上传素材,点击Generate
按钮即可推理:
python inference/app_real3dportrait.py
Google Colab推理
运行这个Colab中的所有cell。
命令行推理
首先,切换至项目根目录并启用Conda环境:
cd <Real3DPortraitRoot>
conda activate real3dportrait
export PYTHON_PATH=./
音频驱动场景下,需要至少提供source image与driving audio,推理指令:
python inference/real3d_infer.py \
--src_img <PATH_TO_SOURCE_IMAGE> \
--drv_aud <PATH_TO_AUDIO> \
--drv_pose <PATH_TO_POSE_VIDEO, OPTIONAL> \
--bg_img <PATH_TO_BACKGROUND_IMAGE, OPTIONAL> \
--out_name <PATH_TO_OUTPUT_VIDEO, OPTIONAL>
视频驱动场景下,需要至少提供source image与driving expression video(作为drv_aud参数),推理指令:
python inference/real3d_infer.py \
--src_img <PATH_TO_SOURCE_IMAGE> \
--drv_aud <PATH_TO_EXP_VIDEO> \
--drv_pose <PATH_TO_POSE_VIDEO, OPTIONAL> \
--bg_img <PATH_TO_BACKGROUND_IMAGE, OPTIONAL> \
--out_name <PATH_TO_OUTPUT_VIDEO, OPTIONAL>
一些可选参数注释:
--drv_pose
指定时提供了运动pose信息,不指定则为静态运动--bg_img
指定时提供了背景信息,不指定则为source image提取的背景--mouth_amp
嘴部张幅参数,值越大张幅越大--map_to_init_pose
值为True
时,首帧的pose将被映射到source pose,后续帧也作相同变换--temperature
代表audio2motion的采样温度,值越大结果越多样,但同时精确度越低--out_name
不指定时,结果将保存在infer_out/tmp/
中--out_mode
值为final
时,只输出说话人视频;值为concat_debug
时,同时输出一些可视化的中间结果
指令示例:
python inference/real3d_infer.py \
--src_img data/raw/examples/Macron.png \
--drv_aud data/raw/examples/Obama_5s.wav \
--drv_pose data/raw/examples/May_5s.mp4 \
--bg_img data/raw/examples/bg.png \
--out_name output.mp4 \
--out_mode concat_debug
ToDo
- Release Pre-trained weights of Real3D-Portrait.
- Release Inference Code of Real3D-Portrait.
- Release Gradio Demo of Real3D-Portrait..
- Release Google Colab of Real3D-Portrait..
- Release Training Code of Real3D-Portrait.
引用我们
如果这个仓库对你有帮助,请考虑引用我们的工作:
@article{ye2024real3d,
title={Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis},
author={Ye, Zhenhui and Zhong, Tianyun and Ren, Yi and Yang, Jiaqi and Li, Weichuang and Huang, Jiawei and Jiang, Ziyue and He, Jinzheng and Huang, Rongjie and Liu, Jinglin and others},
journal={arXiv preprint arXiv:2401.08503},
year={2024}
}
@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}
}
@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}
}