🎬 video

Step-Video-TI2V

A graphic video model based on 30B parameters that supports controllable motion range and various camera effects.

#"视频生成、人工智能、多模态、动漫、特效、运镜"
Step-Video-TI2V

Product Details

Step-Video-TI2V is an advanced graphic video model developed by Shanghai Step Star Intelligent Technology Co., Ltd. It is trained based on Step-Video-T2V with 30B parameters and can generate videos up to 102 frames based on text and image input. The core advantage of this model lies in its two major features: controllable motion amplitude and controllable lens motion, which can balance the dynamics and stability of video generation results. In addition, it performs well in animation-style video generation and is very suitable for application scenarios such as animation creation and short video production. The open source of this model provides powerful technical support for the field of video generation and promotes the development of multi-modal generation technology.

Main Features

1
Supports controllable motion amplitude: Users can control the dynamic level of the video by adjusting the motion score. From static stable images to highly dynamic action scenes, it can meet the needs of creators. The higher the motion score, the more dynamic the video, providing flexible creative space for creators.
2
Multiple camera movement controls: Supports multiple camera movement methods such as fixed lens, pan, pan, zoom, advance, zoom out, rotation, tracking shooting, and surround shooting, etc., and can generate movie-quality videos to meet shooting needs in different scenes.
3
Excellent animation effect: It performs well in animation-style video generation and can generate videos with blurred backgrounds, blinking movements, blowing kisses, and special effects scenes. It is very suitable for application scenarios such as animation creation and short video production.
4
Supports multi-size generation: supports multiple sizes of Tusheng videos. Whether it is the wide field of view of the horizontal screen, the immersive experience of the vertical screen, or the classic retro of the square screen, it can be easily controlled. Users can freely choose the image size according to different creative needs and platform characteristics.
5
High-quality video generation: The generated video has high resolution and smooth dynamic effects, which can meet the needs of professional creators and ordinary users, and provides powerful technical support for video creation.
6
Open source and community support: The model has been open source, and users can download the model weights and inference code on GitHub, which facilitates developers to carry out secondary development and optimization and promotes further development of technology.
7
Technology leadership: In the VBench-I2V benchmark test, Step-Video-TI2V achieved state-of-the-art level performance, verifying its advantages in dynamic scoring to generate video stability and consistency control capabilities.

How to Use

1
1. Download the model: Visit the GitHub page and download the model weights and inference code of Step-Video-TI2V.
2
2. Install dependencies: Use conda to create an environment and install the required Python packages to ensure that the environment is configured correctly.
3
3. Prepare input: Prepare the pictures and text descriptions that need to be generated for the video. The pictures are used as the first frame of the video, and the text descriptions are used to guide the video content.
4
4. Adjust parameters: Set parameters such as motion score and camera movement method according to needs to control the dynamics of the video and the lens effect.
5
5. Run the model: Execute the inference script. The model will generate a video based on the input and save it to the specified path.
6
6. View the results: Open the generated video file and check whether the video content meets expectations. If necessary, further adjust the parameters and regenerate.

Target Users

This product is suitable for video creators, animators, advertising designers, short video bloggers, as well as individuals and businesses who have a need for high-quality video generation. It can help creators quickly generate high-quality video content, improve creative efficiency, reduce production costs, and at the same time provide strong technical support for animation and special effects production.

Examples

Generate anime-style videos: Users can upload a picture of an anime character and describe the character's actions and scenes through text to generate an anime video with dynamic effects.

Create cinematic camera effects: Users can specify the camera movement method, such as the lens surrounding, advancing or zooming out, to generate film-like video clips for use in video production or advertising.

Produce special effects videos: Using the special effects generation capabilities of the model, users can generate special effects scenes such as thunder and lightning, spirit animals, etc. to add fantasy effects to the video.

Quick Access

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Categories

🎬 video
› AI model
› video generation

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