

Omnihuman 1
Overview :
OmniHuman-1 is an end-to-end multimodal conditional human video generation framework that can create human videos based on a single portrait and motion signals (such as audio, video, or a combination of both). This technology overcomes the challenge of high-quality data scarcity through a mixed training strategy and supports images of arbitrary aspect ratios, producing realistic human videos. It excels in handling weak signal inputs, particularly audio, making it suitable for various scenarios, including virtual streaming and video production.
Target Users :
OmniHuman-1 is designed for users who need to generate high-quality human videos, such as virtual streamer developers, video producers, animators, and creators who need to quickly generate video content. It can rapidly produce realistic videos from simple inputs (such as a single image and audio), significantly saving time and costs.
Use Cases
Use OmniHuman-1 to generate natural and fluid speech videos for virtual streamers
Create performance videos for music videos featuring singers, supporting various music styles
Generate realistic movement and expression videos for animated characters
Features
Supports video generation based on a single portrait and audio
Accommodates various aspect ratios of input images (such as headshots, half-body, and full-body)
Supports multiple motion signal inputs (audio, video, or a combination of both)
Generates videos with realistic movements, lighting, and texture details
Supports various music styles and vocal performances
Enables gesture motion generation
Supports input of cartoons, animals, and complex poses
How to Use
Visit the OmniHuman-1 project page (https://omnihuman-lab.github.io/)
Prepare a high-quality portrait image as input
Select an appropriate motion signal (such as an audio file or video file)
Upload the portrait image and motion signal to the model
The model generates corresponding video content based on the inputs
Download the generated video and proceed with further editing or usage
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