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Advising Organization:Ocean Affairs Council
As global attention on marine debris intensifies, leveraging AI to enhance governance efficiency has become a prominent international trend. To accelerate this digital transformation, the National Academy of Marine Research (NAMR) has established an AI-Ready marine debris dataset covering 33+1 distinct categories. To this end, NAMR is hosting the "International AI Challenge on Marine Debris Image Recognition," officially releasing this high-quality dataset this July as a training set for machine learning models. The competition openly invites global talent from fields such as artificial intelligence, computer vision, and marine science to step up to the challenge. By developing high-precision object detection models, participants will turn technological innovation into tangible environmental impact, working together to shape a smarter, more sustainable future for marine governance.
Total prize pool: NT$300,000
| Place | Number of Winners | Prize Money |
| 1st Place | 1 | 120,000 |
| 2nd Place | 1 | 100,000 |
| 3rd Place | 1 | 80,000 |
Best Lightweight Optimization Award (2 winners): Competition Certificate
All event times are based on Taiwan Time (GMT+8).
| Date | Event |
|---|---|
| 2026/09/03 | Announcement of Finalists |
| 2026/09/06 | Final Technical Workshop |
| 2026/09/06 09:00:00 | Test Set Release and Final Submission |
| 2026/09/17 23:59:59 | Deadline for Final Submission |
| 2026/09/30 | Winners Announcement |
The evaluation metric uses mean Average Precision (mAP)[1] at an Intersection over Union (IoU)[2] threshold of 0.5. A prediction bounding box is considered a True Positive (TP) if its IoU with the ground truth bounding box is greater than 0.5; otherwise, it is a False Positive (FP). Precision is then calculated based on TP and FP counts. The system evaluates the AP score for each object type and then averages the AP values across the 19+1 classes of marine debris objects to obtain the final mAP evaluation value, which determines the ranking.
The system uses the COCO API[3] to calculate the mAP values.
Reference
[1] Average Precision (AP): Average precision
[2] intersection over union (IoU): Jaccard index
[3] COCO API: https://github.com/cocodataset/cocoapi
The Best Lightweight Optimization Award uses NetScore as the comprehensive evaluation metric. All teams that advance to the semi-finals and submit a valid model meeting the regulations automatically qualify for this award.
The evaluation formula is as follows:
$$\Omega = 20\log _{10}(\frac{a^2}{(\sqrt{p}\sqrt{m} )} )$$