Underwater Video

Underwater video analysis is rapidly advancing, driven by the need to efficiently extract information from increasingly large and complex datasets captured by various underwater platforms. Current research focuses on developing and benchmarking deep learning models, including transformers and convolutional neural networks, for tasks such as object tracking, video enhancement, and species identification and counting. These advancements are crucial for improving marine research, enabling more efficient monitoring of marine ecosystems, and supporting applications in underwater robotics and conservation efforts. The development of large, publicly available datasets is a key factor driving progress in this field.