The ImageNet competition was launched in 2010. ImageNet is a 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.
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
This year’s ImageNet 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.