MotionDirector

MotionDirector

自定义文本到视频模型的动作生成

MotionDirector是一款文本到视频扩散模型定制工具,可根据视频样本学习特定动作概念并应用于视频生成。该工具支持单个或多个参考视频,能准确捕捉动作特征,实现外观和动作的同步定制。此外,MotionDirector还具备图像动画和电影镜头效果功能,为AI视频创作提供更多可能性。

MotionDirector文本到视频运动定制扩散模型AI视频生成Github开源项目
<p align="center"> <h2 align="center">MotionDirector: Motion Customization of Text-to-Video Diffusion Models</h2> <p align="center"> <a href="https://ruizhaocv.github.io/"><strong>Rui Zhao</strong></a> · <a href="https://ycgu.site/"><strong>Yuchao Gu</strong></a> · <a href="https://zhangjiewu.github.io/"><strong>Jay Zhangjie Wu</strong></a> · <a href="https://junhaozhang98.github.io//"><strong>David Junhao Zhang</strong></a> · <a href="https://jia-wei-liu.github.io/"><strong>Jia-Wei Liu</strong></a> · <a href="https://weijiawu.github.io/"><strong>Weijia Wu</strong></a> · <a href="https://www.jussikeppo.com/"><strong>Jussi Keppo</strong></a> · <a href="https://sites.google.com/view/showlab"><strong>Mike Zheng Shou</strong></a> <br> <br> <a href="https://arxiv.org/abs/2310.08465"><img src='https://img.shields.io/badge/arXiv-2310.08465-b31b1b.svg'></a> <a href='https://showlab.github.io/MotionDirector'><img src='https://img.shields.io/badge/Project_Page-MotionDirector-blue'></a> <a href='https://huggingface.co/spaces/ruizhaocv/MotionDirector'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-yellow'></a> <a href='https://www.youtube.com/watch?v=Wq93zi8bE3U'><img src='https://img.shields.io/badge/Demo_Video-MotionDirector-red'></a> <br> <b>Show Lab, National University of Singapore &nbsp; | &nbsp; Zhejiang University</b> </p> <p align="center"> <img src="https://github.com/showlab/MotionDirector/blob/page/assets/teaser.gif" width="1080px"/> <br> <em>MotionDirector can customize text-to-video diffusion models to generate videos with desired motions.</em> </p>

Task Definition

Motion Customization of Text-to-Video Diffusion Models: </br> Given a set of video clips of the same motion concept, the task of Motion Customization is to adapt existing text-to-video diffusion models to generate diverse videos with this motion.

Demos

Demo Video:

Demo Video of MotionDirector

Customize both Appearance and Motion: <a name="Customize_both_Appearance_and_Motion"></a>

<table class="center"> <tr> <td style="text-align:center;"><b>Reference images or videos</b></td> <td style="text-align:center;" colspan="3"><b>Videos generated by MotionDirector</b></td> </tr> <tr> <td><img src=assets/customized_appearance_results/reference_images.png></td> <td><img src=assets/customized_appearance_results/A_Terracotta_Warrior_is_riding_a_horse_through_an_ancient_battlefield_1455028.gif></td> <td><img src=assets/customized_appearance_results/A_Terracotta_Warrior_is_playing_golf_in_front_of_the_Great_Wall_5804477.gif></td> <td><img src=assets/customized_appearance_results/A_Terracotta_Warrior_is_walking_cross_the_ancient_army_captured_with_a_reverse_follow_cinematic_shot_653658.gif></td> </tr> <tr> <td width=25% style="text-align:center;color:gray;">Reference images for appearance customization: "A Terracotta Warrior on a pure color background."</td> <td width=25% style="text-align:center;">"A Terracotta Warrior is riding a horse through an ancient battlefield."</br> seed: 1455028</td> <td width=25% style="text-align:center;">"A Terracotta Warrior is playing golf in front of the Great Wall." </br> seed: 5804477</td> <td width=25% style="text-align:center;">"A Terracotta Warrior is walking cross the ancient army captured with a reverse follow cinematic shot." </br> seed: 653658</td> </tr> <tr> <td><img src=assets/multi_videos_results/reference_videos.gif></td> <td><img src=assets/customized_appearance_results/A_Terracotta_Warrior_is_riding_a_bicycle_past_an_ancient_Chinese_palace_166357.gif></td> <td><img src=assets/customized_appearance_results/A_Terracotta_Warrior_is_lifting_weights_in_front_of_the_Great_Wall_5635982.gif></td> <td><img src=assets/customized_appearance_results/A_Terracotta_Warrior_is_skateboarding_9033688.gif></td> </tr> <tr> <td width=25% style="text-align:center;color:gray;">Reference videos for motion customization: "A person is riding a bicycle."</td> <td width=25% style="text-align:center;">"A Terracotta Warrior is riding a bicycle past an ancient Chinese palace."</br> seed: 166357.</td> <td width=25% style="text-align:center;">"A Terracotta Warrior is lifting weights in front of the Great Wall." </br> seed: 5635982</td> <td width=25% style="text-align:center;">"A Terracotta Warrior is skateboarding." </br> seed: 9033688</td> </tr> </table>

News

ToDo

  • Gradio Demo
  • More trained weights of MotionDirector

Model List

TypeTraining DataDescriptionsLink
MotionDirector for SportsMultiple videos for each model.Learn motion concepts of sports, i.e. lifting weights, riding horse, palying golf, etc.Link
MotionDirector for Cinematic ShotsA single video for each model.Learn motion concepts of cinematic shots, i.e. dolly zoom, zoom in, zoom out, etc.Link
MotionDirector for Image AnimationA single image for spatial path. And a single video or multiple videos for temporal path.Animate the given image with learned motions.Link
MotionDirector with Customized AppearanceA single image or multiple images for spatial path. And a single video or multiple videos for temporal path.Customize both appearance and motion in video generation.Link

Setup

Requirements

# create virtual environment conda create -n motiondirector python=3.8 conda activate motiondirector # install packages pip install -r requirements.txt

Weights of Foundation Models

git lfs install ## You can choose the ModelScopeT2V or ZeroScope, etc., as the foundation model. ## ZeroScope git clone https://huggingface.co/cerspense/zeroscope_v2_576w ./models/zeroscope_v2_576w/ ## ModelScopeT2V git clone https://huggingface.co/damo-vilab/text-to-video-ms-1.7b ./models/model_scope/

Weights of trained MotionDirector <a name="download_weights"></a>

# Make sure you have git-lfs installed (https://git-lfs.com) git lfs install git clone https://huggingface.co/ruizhaocv/MotionDirector_weights ./outputs # More and better trained MotionDirector are released at a new repo: git clone https://huggingface.co/ruizhaocv/MotionDirector ./outputs # The usage is slightly different, which will be updated later.

Usage

Training

Train MotionDirector on multiple videos:

python MotionDirector_train.py --config ./configs/config_multi_videos.yaml

Train MotionDirector on a single video:

python MotionDirector_train.py --config ./configs/config_single_video.yaml

Note:

  • Before running the above command, make sure you replace the path to foundational model weights and training data with your own in the config files config_multi_videos.yaml or config_single_video.yaml.
  • Generally, training on multiple 16-frame videos usually takes 300~500 steps, about 9~16 minutes using one A5000 GPU. Training on a single video takes 50~150 steps, about 1.5~4.5 minutes using one A5000 GPU. The required VRAM for training is around 14GB.
  • Reduce n_sample_frames if your GPU memory is limited.
  • Reduce the learning rate and increase the training steps for better performance.

Inference

python MotionDirector_inference.py --model /path/to/the/foundation/model --prompt "Your prompt" --checkpoint_folder /path/to/the/trained/MotionDirector --checkpoint_index 300 --noise_prior 0.

Note:

  • Replace /path/to/the/foundation/model with your own path to the foundation model, like ZeroScope.
  • The value of checkpoint_index means the checkpoint saved at which the training step is selected.
  • The value of noise_prior indicates how much the inversion noise of the reference video affects the generation. We recommend setting it to 0 for MotionDirector trained on multiple videos to achieve the highest diverse generation, while setting it to 0.1~0.5 for MotionDirector trained on a single video for faster convergence and better alignment with the reference video.

Inference with pre-trained MotionDirector

All available weights are at official Huggingface Repo. Run the download command, the weights will be downloaded to the folder outputs, then run the following inference command to generate videos.

MotionDirector trained on multiple videos:

python MotionDirector_inference.py --model /path/to/the/ZeroScope --prompt "A person is riding a bicycle past the Eiffel Tower." --checkpoint_folder ./outputs/train/riding_bicycle/ --checkpoint_index 300 --noise_prior 0. --seed 7192280

Note:

  • Replace /path/to/the/ZeroScope with your own path to the foundation model, i.e. the ZeroScope.
  • Change the prompt to generate different videos.
  • The seed is set to a random value by default. Set it to a specific value will obtain certain results, as provided in the table below.

Results:

<table class="center"> <tr> <td style="text-align:center;"><b>Reference Videos</b></td> <td style="text-align:center;" colspan="3"><b>Videos Generated by MotionDirector</b></td> </tr> <tr> <td><img src=assets/multi_videos_results/reference_videos.gif></td> <td><img src=assets/multi_videos_results/A_person_is_riding_a_bicycle_past_the_Eiffel_Tower_7192280.gif></td> <td><img src=assets/multi_videos_results/A_panda_is_riding_a_bicycle_in_a_garden_2178639.gif></td> <td><img src=assets/multi_videos_results/An_alien_is_riding_a_bicycle_on_Mars_2390886.gif></td> </tr> <tr> <td width=25% style="text-align:center;color:gray;">"A person is riding a bicycle."</td> <td width=25% style="text-align:center;">"A person is riding a bicycle past the Eiffel Tower.” </br> seed: 7192280</td> <td width=25% style="text-align:center;">"A panda is riding a bicycle in a garden." </br> seed: <s>2178639</s> </td> <td width=25% style="text-align:center;">"An alien is riding a bicycle on Mars." </br> seed: 2390886</td> </table>

MotionDirector trained on a single video:

16 frames:

python MotionDirector_inference.py --model /path/to/the/ZeroScope --prompt "A tank is running on the moon." --checkpoint_folder ./outputs/train/car_16/ --checkpoint_index 150 --noise_prior 0.5 --seed 8551187
<table class="center"> <tr> <td style="text-align:center;"><b>Reference Video</b></td> <td style="text-align:center;" colspan="3"><b>Videos Generated by MotionDirector</b></td> </tr> <tr> <td><img src=assets/single_video_results/reference_video.gif></td> <td><img src=assets/single_video_results/A_tank_is_running_on_the_moon_8551187.gif></td> <td><img src=assets/single_video_results/A_lion_is_running_past_the_pyramids_431554.gif></td> <td><img src=assets/single_video_results/A_spaceship_is_flying_past_Mars_8808231.gif></td> </tr> <tr> <td width=25% style="text-align:center;color:gray;">"A car is running on the road."</td> <td width=25% style="text-align:center;">"A tank is running on the moon.” </br> seed: 8551187</td> <td width=25% style="text-align:center;">"A lion is running past the pyramids." </br> seed: 431554</td> <td width=25% style="text-align:center;">"A spaceship is flying past Mars." </br> seed: 8808231</td> </tr> </table>

24 frames:

python MotionDirector_inference.py --model /path/to/the/ZeroScope --prompt "A truck is running past the Arc de Triomphe." --checkpoint_folder ./outputs/train/car_24/ --checkpoint_index 150 --noise_prior 0.5 --width 576 --height 320 --num-frames 24 --seed 34543
<table class="center"> <tr> <td style="text-align:center;"><b>Reference Video</b></td> <td style="text-align:center;" colspan="3"><b>Videos Generated by MotionDirector</b></td> </tr> <tr> <td><img src=assets/single_video_results/24_frames/reference_video.gif></td> <td><img src=assets/single_video_results/24_frames/A_truck_is_running_past_the_Arc_de_Triomphe_34543.gif></td> <td><img src=assets/single_video_results/24_frames/An_elephant_is_running_in_a_forest_2171736.gif></td> </tr> <tr> <td width=25% style="text-align:center;color:gray;">"A car is running on the road."</td> <td width=25% style="text-align:center;">"A truck is running past the Arc de Triomphe.” </br> seed: 34543</td> <td width=25% style="text-align:center;">"An elephant is running in a forest." </br> seed: 2171736</td> </tr> <tr> <td><img src=assets/single_video_results/24_frames/reference_video.gif></td> <td><img src=assets/single_video_results/24_frames/A_person_on_a_camel_is_running_past_the_pyramids_4904126.gif></td> <td><img

编辑推荐精选

问小白

问小白

全能AI智能助手,随时解答生活与工作的多样问题

问小白,由元石科技研发的AI智能助手,快速准确地解答各种生活和工作问题,包括但不限于搜索、规划和社交互动,帮助用户在日常生活中提高效率,轻松管理个人事务。

热门AI助手AI对话AI工具聊天机器人
Transly

Transly

实时语音翻译/同声传译工具

Transly是一个多场景的AI大语言模型驱动的同声传译、专业翻译助手,它拥有超精准的音频识别翻译能力,几乎零延迟的使用体验和支持多国语言可以让你带它走遍全球,无论你是留学生、商务人士、韩剧美剧爱好者,还是出国游玩、多国会议、跨国追星等等,都可以满足你所有需要同传的场景需求,线上线下通用,扫除语言障碍,让全世界的语言交流不再有国界。

讯飞智文

讯飞智文

一键生成PPT和Word,让学习生活更轻松

讯飞智文是一个利用 AI 技术的项目,能够帮助用户生成 PPT 以及各类文档。无论是商业领域的市场分析报告、年度目标制定,还是学生群体的职业生涯规划、实习避坑指南,亦或是活动策划、旅游攻略等内容,它都能提供支持,帮助用户精准表达,轻松呈现各种信息。

AI办公办公工具AI工具讯飞智文AI在线生成PPTAI撰写助手多语种文档生成AI自动配图热门
讯飞星火

讯飞星火

深度推理能力全新升级,全面对标OpenAI o1

科大讯飞的星火大模型,支持语言理解、知识问答和文本创作等多功能,适用于多种文件和业务场景,提升办公和日常生活的效率。讯飞星火是一个提供丰富智能服务的平台,涵盖科技资讯、图像创作、写作辅助、编程解答、科研文献解读等功能,能为不同需求的用户提供便捷高效的帮助,助力用户轻松获取信息、解决问题,满足多样化使用场景。

热门AI开发模型训练AI工具讯飞星火大模型智能问答内容创作多语种支持智慧生活
Spark-TTS

Spark-TTS

一种基于大语言模型的高效单流解耦语音令牌文本到语音合成模型

Spark-TTS 是一个基于 PyTorch 的开源文本到语音合成项目,由多个知名机构联合参与。该项目提供了高效的 LLM(大语言模型)驱动的语音合成方案,支持语音克隆和语音创建功能,可通过命令行界面(CLI)和 Web UI 两种方式使用。用户可以根据需求调整语音的性别、音高、速度等参数,生成高质量的语音。该项目适用于多种场景,如有声读物制作、智能语音助手开发等。

Trae

Trae

字节跳动发布的AI编程神器IDE

Trae是一种自适应的集成开发环境(IDE),通过自动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。

AI工具TraeAI IDE协作生产力转型热门
咔片PPT

咔片PPT

AI助力,做PPT更简单!

咔片是一款轻量化在线演示设计工具,借助 AI 技术,实现从内容生成到智能设计的一站式 PPT 制作服务。支持多种文档格式导入生成 PPT,提供海量模板、智能美化、素材替换等功能,适用于销售、教师、学生等各类人群,能高效制作出高品质 PPT,满足不同场景演示需求。

讯飞绘文

讯飞绘文

选题、配图、成文,一站式创作,让内容运营更高效

讯飞绘文,一个AI集成平台,支持写作、选题、配图、排版和发布。高效生成适用于各类媒体的定制内容,加速品牌传播,提升内容营销效果。

热门AI辅助写作AI工具讯飞绘文内容运营AI创作个性化文章多平台分发AI助手
材料星

材料星

专业的AI公文写作平台,公文写作神器

AI 材料星,专业的 AI 公文写作辅助平台,为体制内工作人员提供高效的公文写作解决方案。拥有海量公文文库、9 大核心 AI 功能,支持 30 + 文稿类型生成,助力快速完成领导讲话、工作总结、述职报告等材料,提升办公效率,是体制打工人的得力写作神器。

openai-agents-python

openai-agents-python

OpenAI Agents SDK,助力开发者便捷使用 OpenAI 相关功能。

openai-agents-python 是 OpenAI 推出的一款强大 Python SDK,它为开发者提供了与 OpenAI 模型交互的高效工具,支持工具调用、结果处理、追踪等功能,涵盖多种应用场景,如研究助手、财务研究等,能显著提升开发效率,让开发者更轻松地利用 OpenAI 的技术优势。

下拉加载更多