The exponential growth of marine litter calls for a state-of-the-art detection and collection solutions in real-time. This chapter presents the enhanced underwater trash detection using the YOLOv11 network and ESRGAN. It provides a method for enhancing underwater images degraded with blurring and low visibility, along with refraction of light, thus improving visibility of objects within such water, which will enable YOLOv11 to detect marine debris quickly. With superior precision, recall, and mAP, the model excels in detecting small and partially occluded objects beyond what the current systems can do. This dual-pronged effort upgrades environmental monitoring, supports focused cleanup operations, and promotes marine conservation efforts. The study provides a strong framework in addressing underwater pollution, which is increasingly becoming a threat to environmental sustainability and marine biodiversity.