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Synthetic data getting serious for biometrics training

And silly for memes
Categories Biometric R&D  |  Biometrics News
Synthetic data getting serious for biometrics training

Synthetic data created by artificial intelligence systems, for AI systems is a growing market, as general adversarial networks (GANs) are used to train facial recognition and other biometric algorithms.

The Washington Post profiles a company called Yuty, and the path it took to providing synthetic facial datasets, and reports that it is one of around 50 startups in the space.

The Post notes that Gartner has forecast 60 percent of all AI training data will be synthetic by 2024.

Amazon recently revealed that it relied heavily on synthetic data to train its palm biometrics.

In a similar vein, OpenAI’s DALL-E machine learning tool has updated a policy to allow its users to share synthetic facial images, after the tool’s developers built in mechanisms to prevent its use in creating deepfakes, according to Vice.

DALL-E is not actually intended to generate photorealistic faces, however. The tool’s name is a portmanteau of surrealist painter Salvador Dali and animated movie character WALL-E. Instead, the tool is mostly being used to generate memes.

Datatang at CPVR 2022

Datatang brough its synthetic data generation technology to the 2022 Conference on Computer Vision and Pattern Recognition (CVPR 2022) as a silver sponsor of the event, and held a giveaway to help improve the state of the art in biometric liveness detection and spoof prevention.

The company gave away $20,000 worth of biometric training data in the form of 5 datasets for 3D liveness detection, 2D spoof detection, and re-identification system training.

“We hope this training datasets could help research institutions and tech companies improve their AI models,” explains Datatang International Marketing Manager Frank Wang in an email to Biometric Update.

“As the top conference in the field of computer vision, CVPR attracts a large number of professionals from the fields of artificial intelligence, computer vision and machine learning around the world every year,” Wang writes. “Since the outbreak of epidemic, CVPR 2022 has restarted offline participation for the first time. The number of paper submission has reached nearly 10,000, an increase of 15 percent compared with last year, of which 44.59 percent of the authors are from China mainland.

“The paper ‘EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation’ by researchers from Alibaba and Tongji University won the Best Student Paper Award.”

There were 250 presentations at CPVR 2022 this year, which was held June 21 to 24, along with 66 workshops and 29 tutorials.

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