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Description
This system utilizes a sophisticated multi-stage diffusion model for converting text descriptions into corresponding video content, exclusively processing input in English.
The framework is composed of three interconnected sub-networks: one for extracting text features, another for transforming these features into a video latent space, and a final network that converts the latent representation into a visual video format.
With approximately 1.7 billion parameters, this model is designed to harness the capabilities of the Unet3D architecture, enabling effective video generation through an iterative denoising method that begins with pure Gaussian noise.
This innovative approach allows for the creation of dynamic video sequences that accurately reflect the narratives provided in the input descriptions.
Description
The NVIDIA Synthetic Video Detector is an advanced microservice powered by AI, specifically created to assess whether a video is genuine or generated by artificial intelligence. Its primary focus is on content generated through diffusion models, making it particularly suitable for applications in media authentication, digital forensics, content verification, broadcast processes, and ensuring the integrity of media. The tool evaluates MP4 video inputs and provides a prediction for each individual frame on a continuum from 0 to 1; where values leaning towards 0 suggest authenticity and those nearing 1 indicate synthetic origins. Furthermore, it is engineered to maintain its effectiveness even under typical video compression scenarios, which helps in sustaining reliable detection capabilities after the footage has undergone processing or distribution via standard media channels. Utilizing a Vision Transformer architecture that incorporates an ensemble of DINOv2 and DINOv3 backbones, it adeptly merges visual representations to differentiate between real and artificially created video content. Input frames are resized to 504 x 504 pixels and subjected to normalization prior to the inference process, ensuring optimal performance in the analysis. This sophisticated approach enables a robust assessment of video authenticity, making it a vital tool in the evolving landscape of digital media verification.
API Access
Has API
No
API Access
Has API
Yes
Integrations
GLM-4.5
Yes
Pumli
Yes
Qwen
Yes
Qwen 4
Yes
Qwen-Image
Yes
Qwen2
Yes
Qwen2-VL
Yes
Qwen2.5
Yes
Qwen2.5-1M
Yes
Qwen2.5-Coder
Yes
Integrations
GLM-4.5
No
Pumli
No
Qwen
No
Qwen 4
No
Qwen-Image
No
Qwen2
No
Qwen2-VL
No
Qwen2.5
No
Qwen2.5-1M
No
Qwen2.5-Coder
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Alibaba Cloud
Country
China
Website
modelscope.cn/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
build.nvidia.com/nvidia/synthetic-video-detector
