Enterprise Plans
AI Application Development
AI Translator API
AI SEO/GEO Service
Web Scraping Service
Log in
const main = async () => {
const response = await fetch('https://api.ai.cc/v2/video/generations', {
method: 'POST',
headers: {
Authorization: 'Bearer ',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'bytedance/omnihuman',
image_url: 'https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg',
audio_url: 'https://storage.googleapis.com/falserverless/example_inputs/omnihuman_audio.mp3',
}),
}).then((res) => res.json());
console.log('Generation:', response);
};
main()
import requests
def main():
url = "https://api.ai.cc/v2/video/generations"
payload = {
"model": "bytedance/omnihuman",
"image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
"audio_url": "https://storage.googleapis.com/falserverless/example_inputs/omnihuman_audio.mp3",
}
headers = {"Authorization": "Bearer ", "Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
print("Generation:", response.json())
if __name__ == "__main__":
main()
-
AI Playground
Test all API models in the sandbox environment before you integrate.
We provide more than 300 models to integrate into your app.
Product Detail
OmniHuman is an advanced AI model developed by ByteDance for generating personalized realistic full-body videos from a single photo and an audio clip (speech or vocals). The model produces videos of arbitrary length with customizable aspect ratios and body proportions, animating not just the face but the entire body, including gestures and facial expressions synchronized precisely with speech.
✨ Technical Specifications
- Synchronization: Advanced lip-sync technology tightly matches audio speech with mouth movement and facial expression.
- Motion Dynamics: Diffusion transformer predicts and refines frame-to-frame body motion for smooth, lifelike animation.
- Multi-condition training: Combines audio, pose, and text inputs for precise motion prediction.
- User Interface: Easy-to-use platform with upload, generation, and download features designed for professional and casual users.
📊 Performance Benchmarks
- Achieves highly realistic video generation with natural lip sync, facial expressions, and full-body gestures.
- Outperforms traditional deepfake technologies focusing mostly on faces, by animating the entire body.
- Smooth transitions and accurate speech-motion alignment confirmed by extensive internal testing on thousands of video samples.
- Supports creation of longer videos without loss of synchronization or motion naturalness.
💰 API Pricing
$0.126 /second
🚀 Key Features
- Customizable video length and aspect ratio: Allows creating videos of any duration and resizing body proportions.
- High fidelity and naturalness: Trained on over 18,700 hours of video data to master nuanced gestures, expressions, and motion dynamics.
- Multi-style compatibility: Works with portrait, half-body, or full-body images, including realistic photos and stylized poses.
💡 Use Cases
- Creating realistic digital avatars for marketing, entertainment, and social media.
- Generating full-body video avatars for virtual events and presentations.
- Producing AI-driven characters for games, films, and virtual production.
- Enhancing distance learning and online education with animated lecturers.
- Synchronizing dubbing and voiceovers with realistic lip-sync video avatars.
💻 Code Sample
<snippet data-name="bytedance.create-omnihuman-image-to-video-generation" data-model="bytedance/omnihuman"></snippet>
↔️ Comparison with Other Models
vs Meta Make-A-Video: OmniHuman uses multimodal inputs (audio, image, video) for precise full-body human animation, enabling detailed gestures and expressions. Meta Make-A-Video generates short videos from text prompts, mainly focusing on creative content rather than realistic human motion.
vs Synthesia: OmniHuman produces realistic, full-length, full-body videos with natural lip sync and body gestures, targeting diverse professional applications. Synthesia specializes in talking head avatars with upper body animation, optimized for business presentations and e-learning with more limited motion scope.
⚠️ Ethical Considerations
While OmniHuman offers groundbreaking capabilities, there are risks related to deepfake misuse. Responsible use guidelines and rights management policies are strongly recommended when deploying this technology.
🔗 API Integration
Accessible via AI/ML API. For comprehensive documentation, please refer to the Official OmniHuman API Documentation.
❓ Frequently Asked Questions (FAQ)
What generative architecture enables OmniHuman's photorealistic human synthesis across diverse attributes?
OmniHuman employs a revolutionary compositional generative framework that decomposes human appearance into orthogonal factors including facial geometry, skin texture, hair properties, body morphology, and expressive characteristics. The architecture features disentangled latent representations that allow independent control over demographic attributes, age progression, emotional expressions, and stylistic elements while maintaining biological plausibility. Advanced normalizing flows and diffusion processes ensure photorealistic output quality, while ethical constraints embedded in the training process prevent generation of identifiable individuals without explicit consent.
How does OmniHuman achieve unprecedented diversity and inclusion in synthetic human generation?
The model incorporates comprehensive demographic and phenotypic coverage through curated training data representing global human diversity across ethnicity, age, body types, abilities, and cultural presentations. Sophisticated data augmentation techniques generate continuous variations beyond discrete categories, while fairness constraints in the training objective prevent representation biases. The system includes explicit controls for adjusting representation proportions and ensures equitable generation quality across all demographic segments, making it particularly valuable for creating inclusive visual content and avoiding stereotypical portrayals.
What dynamic generation capabilities distinguish OmniHuman for interactive applications?
OmniHuman supports real-time generation of dynamic human representations with controllable facial expressions, gaze direction, head poses, and body language. The architecture enables seamless interpolation between different attributes, age progression/regression sequences, and emotional expression transitions while maintaining identity consistency. Advanced temporal coherence mechanisms ensure smooth motion and expression changes, making the model suitable for interactive applications like virtual avatars, conversational agents, and dynamic content creation where human representations need to adapt in real-time to user interactions.
How does the model ensure ethical generation and prevent potential misuse?
OmniHuman incorporates multiple ethical safeguards including biometric similarity detection that prevents recreation of existing individuals, content moderation systems that filter inappropriate requests, diversity enforcement mechanisms that prevent generation of homogeneous outputs, and transparency features that clearly identify synthetic content. The model's training includes explicit objectives for fair representation across demographic groups, and the deployment framework includes usage monitoring and restrictions for sensitive applications. These measures ensure responsible use while maintaining the model's creative and practical utility.
Learn how you can transformyour company with AICC APIs
