ACM ICMR 2021 Grand Challenge: PAIR Competition歡迎踴躍報名參加！
Embedded Deep Learning Object Detection Model Compression Competition for Traffic in Asian Countries
Competition Start Date:
Object detection in the computer vision area has been extensively studied and making tremendous progress in recent years using deep learning methods. However, due to the heavy computation required in most deep learning-based algorithms, it is hard to run these models on embedded systems, which have limited computing capabilities. In addition, the existing open datasets for object detection applied in ADAS applications usually include pedestrian, vehicles, cyclists, and motorcycle riders in western countries, which is not quite similar to the crowded Asian countries like Taiwan with lots of motorcycle riders speeding on city roads, such that the object detection models training by using the existing open datasets cannot be applied in detecting moving objects in Asian countries like Taiwan.
In this competition, we encourage the participants to design object detection models that can be applied in Taiwan’s traffic with lots of fast speeding motorcycles running on city roads along with vehicles and pedestrians. The developed models not only fit for embedded systems but also achieve high accuracy at the same time.
According to the points of each team in the final evaluation, we select the highest three teams for regular awards.
- Champion: $USD 1,500
- 1st Runner-up: $USD 1,000
- 3rd-place $USD 750
- Best accuracy award – award for the highest mAP in the final competition: $USD 200;
- Best bicycle detection award – award for the highest AP of bicycle recognition in the final competition: $USD 200;
- Best scooter detection award – award for the highest AP of scooter recognition in the final competition: $USD 200;
All the award winners must agree to submit contest paper and attend the ACM ICMR2021 Grand Challenge PAIR Competition Special Session to present their work.