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/generate/video/google/generation', {
method: 'POST',
headers: {
Authorization: 'Bearer ',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'google/veo-3.0-i2v',
image_url: 'https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg',
prompt: 'Mona Lisa puts on glasses with her hands.',
}),
}).then((res) => res.json());
console.log('Generation:', response);
};
main()
import requests
def main():
url = "https://api.ai.cc/v2/generate/video/google/generation"
payload = {
"model": "google/veo-3.0-i2v",
"prompt": "Mona Lisa puts on glasses with her hands.",
"image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
}
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
Google's Veo 3.0 is an advanced AI-driven video generation model meticulously designed for immersive audiovisual content creation. It combines cutting-edge image-to-video synthesis with native audio generation, delivering high-quality cinematic videos with perfectly synchronized sound for both professional and creative applications.
⚙️Technical Specification
Veo 3.0 Image-to-Video is engineered for seamless integration of visual and audio elements with high-resolution output, pushing the boundaries of AI video generation.
- • Video Resolution: Up to 4K quality, fully supporting Full HD standards for crisp visuals.
- • Video Length: Typically 8 seconds per generation, perfect for short, impactful clips.
- • Audio Processing: Real-time synchronized dialogue, sound effects, and ambient audio for a complete experience.
- • Frame Rate: Cinematic-quality motion featuring advanced physics and natural movement simulation.
💰API Pricing
• Standard Generation: 0.21$ per second
• With Audio Integration: 0.42$ per second
✨Key Capabilities
- ➡️ Native Audio Generation: Produces fully synchronized audio tracks, including dialogue, sound effects, and background music, directly within the generation process.
- ➡️ Advanced Lip-Sync: Ensures precise mouth movements perfectly aligned with any generated speech, enhancing realism and viewer engagement.
- ➡️ Multimodal Input: Supports rich text prompts alongside image references for highly detailed video guidance and creative control.
- ➡️ Character Consistency: Maintains visual continuity of characters and objects across diverse scenes and varying camera angles.
- ➡️ Cinematic Controls: Provides professional camera movement, framing, and direction features, empowering creators with film-grade artistry.
- ➡️ Physics Simulation: Generates realistic physics-based motion and interactions for objects and characters, adding an unparalleled layer of authenticity.
🚀Optimal Use Cases
- ✅ Marketing and Social Media Content: Create engaging promotional videos and platform-optimized formats effortlessly.
- ✅ Entertainment: Ideal for crafting short films, music videos, and innovative narrative storytelling experiences.
- ✅ Education: Develop interactive learning content enriched with detailed audiovisual narration.
- ✅ Professional Filmmaking: Leverage for pre-visualization, storyboarding, and rapid concept development in film production.
💻Code Sample & API Reference
For detailed implementation and API usage, refer to the official documentation:
API References: Video Models - Google Veo 3.0 Image-to-Video
Example snippet for `google.create-image-to-video-generation` with `google/veo-3.0-i2v` model.
# Python example (conceptual)
from google.veo import VeoClient
client = VeoClient(api_key="YOUR_API_KEY")
response = client.create_image_to_video_generation(
image_url="https://example.com/static-image.jpg",
prompt="A serene landscape with a river flowing gently, cinematic wide shot.",
model="google/veo-3.0-i2v",
duration_seconds=8,
include_audio=True
)
print(response.video_url)
⚖️Comparison with Other Models
- ➡️ Vs. OpenAI Sora: Veo 3.0 offers native synchronized audio versus Sora's silent outputs, providing a complete audiovisual experience out-of-the-box.
- ➡️ Vs. Runway ML: Features a superior integrated audio-visual workflow, eliminating the need for separate post-production audio syncing processes.
- ➡️ Vs. Pika Labs: Provides enhanced physics simulation and professional-grade cinematic camera controls, resulting in more realistic and polished video outputs.
❓Frequently Asked Questions (FAQs)
What neural architecture enables Veo 3.0 I2V's photorealistic image-to-video transformation?
Veo 3.0 I2V utilizes a cascaded refinement architecture with specialized motion priors that analyze static images to infer plausible temporal evolution. The system combines spatial-temporal transformers with optical flow prediction networks, enabling it to understand object relationships and generate physically accurate motion trajectories. A novel appearance-flow disentanglement mechanism separates content preservation from motion generation, allowing the model to maintain image fidelity while introducing dynamic elements that respect the original scene composition and lighting conditions.
How does Veo 3.0 achieve its breakthrough in motion plausibility and physical accuracy?
The model incorporates physics-informed neural networks trained on extensive motion capture data and real-world physics simulations. It understands material properties, gravitational effects, fluid dynamics, and biomechanical constraints, ensuring generated motions adhere to physical laws. Advanced temporal coherence algorithms maintain object permanence and consistent lighting throughout sequences, while multi-scale motion priors capture both macro movements and subtle micro-expressions with equal fidelity.
What distinguishes Veo 3.0's approach to preserving original image quality during animation?
Veo 3.0 employs perceptual preservation networks that prioritize maintaining the original image's aesthetic qualities, texture details, and color characteristics. The system uses content-aware motion generation that respects image semantics—recognizing which elements should remain static versus dynamic. Advanced texture propagation algorithms ensure that moving objects maintain their surface properties and lighting interactions, while style-consistent generation preserves artistic elements and photographic characteristics throughout the animation process.
How does the model handle diverse image types from portraits to complex landscapes?
The architecture features domain-adaptive processing pathways that automatically detect image categories and apply specialized generation strategies. For portraits, it understands facial anatomy and emotional expression dynamics; for landscapes, it models environmental elements like water flow, cloud movement, and vegetation sway; for architectural scenes, it comprehends structural integrity and perspective consistency. Each pathway incorporates category-specific motion vocabularies and preservation priorities tailored to the unique characteristics of different image types.
What creative control and customization options does Veo 3.0 I2V provide?
Veo 3.0 offers granular motion control through intuitive interfaces including motion direction specification, intensity adjustment, temporal pacing controls, and style transfer options. Users can define specific element behaviors, apply cinematic camera movements, adjust motion realism levels from subtle to dramatic, and combine multiple motion types within single sequences. The system provides real-time previews with adjustable parameters and supports iterative refinement based on visual feedback and specific creative requirements.
Learn how you can transformyour company with AICC APIs
