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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: 'alibaba/wan2.2-vace-fun-a14b-outpainting',
prompt: 'Mona Lisa puts on glasses with her hands.',
video_url: 'https://storage.googleapis.com/falserverless/example_inputs/wan_animate_input_video.mp4',
image_url: 'https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg',
resolution: "720p",
}),
}).then((res) => res.json());
console.log('Generation:', response);
};
main()
import requests
def main():
url = "https://api.ai.cc/v2/video/generations"
payload = {
"model": "alibaba/wan2.2-vace-fun-a14b-outpainting",
"prompt": "Mona Lisa puts on glasses with her hands.",
"video_url": "https://storage.googleapis.com/falserverless/example_inputs/wan_animate_input_video.mp4",
"image_url": "https://s2-111386.kwimgs.com/bs2/mmu-aiplatform-temp/kling/20240620/1.jpeg",
"resolution": "720p",
}
headers = {"Authorization": "Bearer ", "Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
print("Generation:", response.json())
if __name__ == "__main__":
main()
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Product Detail
Wan 2.2 VACE Outpainting is an advanced video-to-video AI model engineered to extend video frames seamlessly beyond their original boundaries. This innovative solution generates additional scene content that harmonizes perfectly with the input video, offering unparalleled creative video outpainting capabilities. Users benefit from flexible control over content style, motion continuity, and resolution quality, making it a key component of the versatile Wan VACE series for video synthesis and editing tasks.
⚙️ Technical Specifications
- Model Architecture: Wan 2.2 VACE Fun A14B, built on advanced video generation and diffusion networks with VACE architecture.
- Input Types: Video files or URLs, supporting various encoding options.
- Output Resolution: Flexible options including 480p, 580p, 720p, and up to 4K.
- Video Frame Rate: Standard 16 FPS; capable of supporting higher frame rates for smoother playback.
- Memory & Performance: Optimized for GPU execution, with model variants suitable for 8 GB VRAM GPUs.
- Max Video Length: Effectively unlimited length capability while preserving temporal consistency.
- Training Data: Trained on extensive video datasets with multi-condition controls for robust and versatile output.
✨ Performance Benchmarks
- State-of-the-Art Quality: Consistently ranked among leading open-source video generation models for its output fidelity.
- Temporal Coherence: Maintains smooth motion and visual consistency across extended frames, crucial for realistic video.
- Resolution Fidelity: Achieves high retention of detail in both spatial and temporal dimensions, even beyond initial frame borders.
- Efficiency: Offers real-time or near real-time generation speeds for standard HD video processing, enhancing productivity.
- Compatibility: Runs efficiently on consumer-grade GPUs with standard 8GB VRAM, making it accessible to a wider user base.
✅ Key Features
- Video Outpainting: Extends video frames with new, contextually relevant content, preserving visual coherence and temporal structure.
- High-Resolution Output: Supports up to 4K resolution output with impeccably smooth frame transitions.
- Flexible Input: Accepts a broad range of video formats including MP4, MOV, WEBM, M4V, and GIF, ensuring broad compatibility.
- Optimal Frame Rate: Processes videos at 16 or more frames per second, ensuring fluid and lifelike motion.
- Advanced Control Conditions: Supports detailed control inputs such as pose, depth, edge (Canny), MLSD, and trajectory control for precise content generation.
- Multilingual Support: Designed to accommodate diverse language inputs, facilitating global application and accessibility.
💲 API Pricing
- 360p: $0.0525
- 540p: $0.07875
- 720p: $0.105
💡 Use Cases
- Creative video outpainting for extending cinematic scenes, enhancing narrative depth.
- Visual effects augmentation in post-production workflows, simplifying complex scene expansions.
- Generating expanded video environments for immersive VR/AR experiences.
- Enhancing video storytelling with additional visual context, providing richer narratives.
- Efficient video content generation for advertising and social media, adapting content to various aspect ratios.
💻 Code Sample
<!-- Code sample for Alibaba/Wan 2.2 VACE Outpainting API integration would be displayed here. -->
(This area is a placeholder for dynamic code snippets for `alibaba.create-video-to-video-generation` using `alibaba/wan2.2-vace-fun-a14b-outpainting` model.)
⚖️ Comparison with Other Leading Models
Wan 2.2 VACE Outpainting vs. Qwen Video:
Wan 2.2 excels in photorealistic video outpainting with detailed multi-condition controls (pose, depth, trajectory), enabling precise scene expansion. In contrast, Qwen Video models typically focus on artistic and stylized generation, often excelling in anime or creative styles but with less emphasis on photorealism and temporal smoothness. This makes Wan 2.2 a superior choice for consistent realism and fluidity in extended video sequences.
Wan 2.2 VACE Outpainting vs. KLING 2.0:
While KLING 2.0 offers competitive video generation quality, Wan 2.2 surpasses it by integrating a MoE (Mixture of Experts) architecture. This innovation reduces compute requirements by approximately 50% while simultaneously enhancing video detail and motion coherence. Furthermore, Wan 2.2 provides more versatile control parameters for nuanced scene and motion manipulation, making it ideal for professional and commercial video synthesis tasks.
Wan 2.2 VACE Outpainting vs. Haiulo 02:
Haiulo 02 is known for smooth basic video synthesis but lacks the advanced conditioning controls and high-resolution outpainting capabilities that Wan 2.2 robustly supports. Wan 2.2's ability to manage complex group movements and detailed CGI effects offers a significant advantage for movie-quality video extension use cases over Haiulo 02’s simpler workflow.
Wan 2.2 VACE Outpainting vs. Veo 3:
Veo 3 primarily focuses on rapid video generation with less emphasis on outpainting quality and fine control, geared more towards fast content creation. In contrast, Wan 2.2 expertly balances speed with fidelity, delivering high-resolution, temporally consistent outpainting with flexible control inputs that Veo 3 currently lacks.
🔗 API Integration
Wan 2.2 VACE Outpainting is readily accessible via the AI/ML API. Comprehensive documentation is available here for developers.
❓ Frequently Asked Questions (FAQ)
Q: What is Wan 2.2 VACE Outpainting?
A: Wan 2.2 VACE Outpainting is an advanced AI model that extends video frames by generating new, contextually relevant content beyond their original borders, ensuring seamless visual and temporal continuity.
Q: How does Wan 2.2 achieve high temporal coherence?
A: It utilizes a sophisticated VACE architecture and multi-condition controls, trained on large-scale video datasets, to maintain smooth motion and consistent visuals across all extended frames.
Q: Can I control the style and content of the outpainted video?
A: Yes, Wan 2.2 offers flexible control over content style and supports detailed control inputs such as pose, depth, edge (Canny), MLSD, and trajectory for precise generation.
Q: What are the primary benefits of using Wan 2.2 for video outpainting?
A: Key benefits include high-resolution output (up to 4K), state-of-the-art temporal consistency, efficient GPU performance, support for unlimited video length, and versatile creative control for various use cases like cinematic expansion and VR/AR content.
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