This year’s ImageNet, and possibly the last competition, ended with Chinese AI teams’ sweeping victory, yet again.

All the top performers were from China, and more than half of the 27 competing teams were Chinese-based universities or institutes. On the image classification challenge, the prize went to a team called WMW, which included two experts from Beijing-based startup Momenta and another one from Oxford University. Their error rate was 2.25 percent. Another team called DBAT won the title in the object detection challenge, with an accuracy rate at 73.1 percent. DBAT consisted of eight experts from Nanjing University and two from Imperial College London.

Since its launch in 2010, the ImageNet Large Scale Visual Recognition Challenge has become a benchmark AI competition in object category classification and detection on hundreds of object categories and millions of images.

(Photo/bigsnarf.wordpress)

Chinese scientists began to outshine others in 2015. In 2016, Trimps-Soushen, a team supported by the Ministry of Public Security, won in object recognition and detection, while researchers from Nanjing University of Information Science and Technology won in the video identification task.

This is reportedly the last ImageNet challenge after seven years, as image-based recognition has seen drastic improvement over the years and there is less need for the challenge now.

It is believed that the WebVision challenge, jointly-organized by Google Research, Swiss Federal Institute of Technology Zurich, and Carnegie Mellon University, will replace ImageNet. The new challenge will be even more challenging, with emphasis on indentifying uncategorized pictures and even wrong ones. The AI winners of WebVision will hopefully move the field of AI even further forward.