This paper presents an approach for making a dataset using a 3D CAD model for deep learning based underwater object detection and pose estimation. We also introduce a simple pose estimation network for underwater objects. In the experiment, we show that object detection and pose estimation networks trained via our synthetic dataset present a preliminary potential for deep learning based approaches in underwater. Lastly, we show that our synthetic image dataset provides meaningful performance for deep learning models in underwater environments. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.