Marine debris management is entering a new phase of data-driven applications. Converting years of accumulated coastal imagery into actionable tools for surveying, identification, and monitoring has emerged as a critical challenge in the digitalization of ocean governance. Under the guidance of Taiwan's Ocean Affairs Council (OAC), the National Academy of Marine Research (NAMR) is hosting the "2026 International Marine Debris Image Recognition AI Challenge." Featuring a dataset of over 20,000 real-world marine debris images, the competition invites AI, data science, computer vision, and marine science teams from Taiwan and abroad to participate. The competition is supported by Amazon Web Services (AWS) as the AI technology partner, with model evaluation and competition operations managed through the Industrial Technology Research Institute's (ITRI) AIdea AI Co-Creation Platform. Registration is now open. NAMR sets the challenge: bringing AI to the frontlines of ocean governance Marine debris has long been a fundamental issue in coastal environmental governance - and one of the most difficult to address in the field. Coastal debris is diverse in type, scattered in distribution, and frequently degraded by sun exposure, seawater erosion, sand burial, and physical damage, making manual surveys and image interpretation highly labor- and time-intensive. To accelerate digital transformation, NAMR has established MDImageNet, an AI-Ready marine debris image dataset covering the ICC19+1, NAMR26+1, and NAMR33+1 marine debris category schemes. The competition draws on NAMR's existing marine debris image dataset, comprising over 20,000 images annotated with YOLO-format bounding boxes. The dataset covers common coastal waste categories including plastic litter, fishing-related debris, and other anthropogenic waste. A "post-mapping" strategy is adopted: participants first train models using the original class labels provided, then map predictions into 20 official recognition categories during inference, with final scoring based on 19+1 primary marine debris target classes. The competition design confronts teams with the real-world constraints