簡介

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 with the 3-D AVM scene 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 Asian 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.

This competition is divided into two stages: qualification and final competition.

• Qualification competition: all participants submit their answers online. A score is calculated. We will announce the threshold at the beginning of the preliminary round. If participants achieve accuracy above the threshold during the qualification round, they will qualify to participate in the final round.
• Final competition: the final score will be evaluated on MemryX CIM computing platform [4] for the final score.
  

The goal is to design a lightweight deep learning model suitable for constrained embedded system design to deal with traffic in Asian countries like Taiwan. We focus on detection accuracy, model size, computational complexity, performance optimization and the deployment on MemryX CIM SDK platform.

MemryX [4] uses a proprietary, configurable native dataflow architecture, along with at-memory computing that sets the bar for Edge AI processing. The system architecture fundamentally eliminates the data movement bottleneck, while supporting future generations (new hardware, new processes/chemistries and new AI models) — all with the same software.

Given the test image dataset, participants are asked to detect objects belonging to the following four classes {pedestrian, vehicle, scooter, bicycle} in each image, including class, bounding box, and confidence.

Reference

[1] COCO API: https://github.com/cocodataset/cocoapi

[2] Average Precision (AP): https://en.wikipedia.org/wiki/Evaluation_measures_(information_retrieval)#Average_precisio n

[3] Intersection over union (IoU): https://en.wikipedia.org/wiki/Jaccard_index

[4]  MemryX SDK: https://memryx.com/technology/

獎項

All the award winner candidates will be invited to submit contest papers to 2023 ACM Multimedia Asia Workshop for review. According to the paper review results, scoring results of the final competition, as well as the completeness of the submitted documents, the final award winners will be decided and announced. In addition, all the award recipients should attend the ACM Multimedia Asia 2023 Grand Challenge PAIR-LITEON Competition Special Session to present their work, otherwise, the award will be canceled.

According to the above-mentioned evaluation, we select three teams for regular awards, and some teams for the special awards. All the awards might be absent according to the conclusion of the review committee. 

For all AI models winning the awards, LITEON has the right to first negotiate with the award winning teams on the commercialization of their developed models.

Regular Award

1. Champion:            $USD 1500
2. 1^st Runner-up:      $USD 1000
3. 3^rd-place:              $USD 700

Special Award

1. Best pedestrian detection award – a award for the highest AP of pedestrian recognition in the final competition: $USD 300;
2. Best bike detection award – award for the highest AP of bicycle recognition in the final competition: $USD 300;
3. Best motorbike detection award – award for the highest AP of scooter recognition in the final competition: $USD 300;