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3DiVi Inc., founded in 2011, is one of the leading developers of AI and machine learning (ML) technologies for computer vision.
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3DiVi Open-Sourced its TOP NIST FRVT Face SDK

3DiVi, a leading provider of 3D computer vision technology, announced that it has open sourced its face recognition software. This move enables developers around the world to access and utilize the cutting-edge technology in their own projects, driving innovation and advancing the field of computer vision.

3DiVi Face SDK is an open-source library that analyzes images to identify human faces, bodies and skeletal joints. The library is top rated in NIST FRVT with 99.62% face recognition accuracy and is available for C++, Python, C#, and Java programming languages on Windows and Linux. It contains Open Model Improvement and Domain Adaptation Scripts which allows you to improve model performance for your specific tasks.

"We are excited to open source our face recognition software and make it available to developers everywhere," said 3DiVi CEO, Huseyin Sengul. "By open sourcing this technology, we hope to foster collaboration and accelerate the development of new and innovative applications in the field of computer vision."

The 3DiVi face recognition software utilizes deep learning algorithms to accurately and efficiently identify and recognize human faces and skeletal joints in real-time. It has been used in a variety of applications, including security and surveillance, social media, and entertainment.

"The 3DiVi face recognition software has consistently demonstrated strong performance in a variety of settings and we are confident that open sourcing it will lead to even more impressive advancements in the field," said Sengul.

The 3DiVi face recognition software is available now on the company's GitHub page. 3DiVi will also provide support and resources to developers who wish to utilize the technology in their projects.

"We believe in the power of collaboration and are committed to supporting the development community as they work to push the boundaries of what is possible with computer vision technology," said Sengul.