Bolstering Maritime Object Detection with Synthetic Data

For autonomy in the maritime domain, object detection is a very important task, as one needs to perceive surroundings take appropriate action decisions. A large issue and classification shortage of thorough datasets. In this work, our aim reduce problem by introducing pipeline for generation simulated data that matches target thereby achieving more reliable robust performance detector. This easily modifiable allows varying setups would be hard or dangerous collect real life. Furthermore, it enables introduction new classes without issue.