

Go With The Flow
Overview :
Go with the Flow is an innovative video generation technology that achieves efficient control over video diffusion model motion patterns by utilizing distorted noise instead of traditional Gaussian noise. This technology allows for precise control of object and camera movements in videos without modifying the original model architecture, all while maintaining computational efficiency. Key advantages include high efficiency, flexibility, and scalability, making it applicable across various scenarios, such as image-to-video and text-to-video generation. Developed by researchers from institutions like Netflix Eyeline Studios, it offers significant academic value and commercial potential, and is currently available to the public as an open-source tool.
Target Users :
This product is designed for developers, researchers, and creative professionals who require efficient control over video motion patterns, such as post-production filmmakers, animation designers, and AI video generation enthusiasts. It helps users quickly generate video content that meets specific movement requirements, enhancing both creative efficiency and quality.
Use Cases
Transfer the motion pattern of objects from one video to another, creating a new video with the same motion effects.
Add dynamic effects to static images with simple drag-and-drop operations to generate coherent videos.
Generate a video featuring specific camera movements based on text descriptions, such as creating a 3D video that rotates around an object.
Features
Supports image-to-video generation (I2V) and text-to-video generation (T2V)
Enables customization and transfer of motion patterns through distorted noise
Provides various motion control options, including object motion and camera motion
Allows for adjustment of motion pattern intensity via noise degradation for varying levels of control
Compatible with multiple video generation models without altering the original architecture
How to Use
Visit the project homepage to download the open-source code and models.
Prepare input data such as images, videos, or text descriptions.
Select a motion mode, like object motion, camera motion, or a custom motion signal.
Adjust noise degradation parameters to control the intensity of the motion pattern.
Run the model to generate the video, and make any further edits or optimizations as needed.
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