What is FakeCatcher?

Intel has introduced the innovative FakeCatcher technology for deepfake detection, which analyzes the "blood flow" within video pixels to swiftly determine the authenticity of videos in just milliseconds. This cutting-edge system is integrated into popular editing software that content creators and broadcasters regularly use, facilitating the identification of altered content during the editing phase. Additionally, it plays a vital role in vetting user-generated content, ensuring that authenticity verification is an integral part of the upload process. By making deepfake detection universally accessible, it empowers both individuals and organizations to effortlessly confirm the legitimacy of videos. Deepfakes, which constitute synthetic media that misrepresent reality by fabricating actors and actions, pose a significant challenge in today’s digital landscape. While numerous deep learning detection systems focus on analyzing raw data for inconsistencies, FakeCatcher adopts a unique method by identifying genuine markers of authenticity in real footage, emphasizing the subtle evidence of human characteristics, like the slight changes in pixel color due to blood flow. As the heart pumps, the color of our veins changes, generating the distinct data that FakeCatcher leverages to differentiate between authentic and doctored videos. This groundbreaking detection technology marks a substantial advancement in the ongoing battle against the misuse of deepfake technology, providing a beacon of hope in preserving the integrity of visual media. As the prevalence of deepfakes continues to rise, the implementation of such innovative solutions will be essential in safeguarding truth in digital content.

Integrations

No integrations listed.

Screenshots and Video

FakeCatcher Screenshot 1

Company Facts

Company Name:
Intel
Company Location:
United States
Company Website:
www.intel.com/content/www/us/en/newsroom/news/intel-introduces-real-time-deepfake-detector.html#gs.08lxwl

Product Details

Deployment
SaaS
Training Options
Documentation Hub
Support
Web-Based Support

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

FakeCatcher Categories and Features