Last year, Chinese police arrested a man at a pop concert after he was flagged as a criminal suspect by a facial recognition system installed at the venue. The software that called the cops was developed by Shanghai startup Yitu Tech. It was marketed with a stamp of approval from the US government.

Yitu is a top performer on a testing program run by the National Institute of Standards and Technology that’s vital to the fast-growing facial recognition industry. More than 60 companies took part in the most recent rounds of testing. The rankings are dominated by entrants from Russia and China, where governments are bullish about facial recognition and relatively unconcerned about privacy.

“It’s considered the industry standard and users rely on NIST’s benchmark for their business decisions and purchases,” says Shuang Wu, a Yitu research scientist and head of Yitu’s Silicon Valley outpost. “Both Chinese and international customers ask about it.”

Yitu’s technology is in use by police and at subway stations and ATMs. It’s currently ranked first on one of NIST’s two main tests, which challenges algorithms to detect when two photos show the same face. That task is at the heart of systems that check passports or control access to buildings and computer systems.

The next five best-performing companies on that test are Russian or Chinese. When the State Department last June picked Paris-based Idemia to provide software used to screen passport applications, it said it had chosen “the most accurate non-Russian or Chinese software” to manage the 360 million faces it has on file.

In a subsequent round of tests, US startup Ever AI ranked seventh, making it the top-performing company outside Russia and China. “Ever since the NIST results came out there’s been a pretty steady stream of customers,” including new interest from government agencies, says Doug Aley, Ever AI’s CEO.

NIST is an arm of the US Commerce Department with the mission of promoting US competitiveness by advancing the science of measurement. Its Facial Recognition Vendor Test program began in 2000, with the support of the Pentagon, after numerous US agencies became interested in using the technology.

Since then, NIST has tracked the steady improvement in algorithms designed to scrutinize human physiognomy, and developed new testing regimes to keep up. The agency now tests algorithms in a subterranean computer room in Gaithersburg, Maryland, using millions of anonymized mugshots and visa photos sourced from government agencies. Its results show that accuracy has improved significantly since the emergence of the neural network technology driving the tech industry’s current AI obsession.

The other NIST test simulates the way facial recognition is used by police investigators, asking algorithms to search for a specific face in a sea of many others. In 2010, the best software could identify someone in a collection of 1.6 million mugshots about 92 percent of the time. In a late 2018 version of that test the best result was 99.7 percent, a nearly 30-fold reduction in error rate.

The best performer on that test is Microsoft, which was scored by NIST for the first time in November. The next three best entrants were Russian and Chinese, with Yitu fourth. Ever AI came fifth. Of the more than 60 entrants listed in NIST’s most recent reports whose home base could be identified, 13 were from the US, 12 from China, and 7 from Russia.