Underwater Datasets

Underwater datasets are crucial for advancing computer vision and robotics in aquatic environments, primarily focusing on improving object detection, semantic SLAM, and 3D mapping capabilities. Current research emphasizes developing large, diverse synthetic and real-world datasets to address challenges like low visibility and variable lighting conditions, often employing techniques like sensor fusion (radar-camera), domain adaptation, and attention mechanisms within models such as YOLOv3 and R-CNN variants. These advancements are vital for enabling autonomous underwater vehicles (AUVs) for applications ranging from marine resource management and environmental monitoring to infrastructure inspection and search and rescue operations.