Underwater Object Detection and Pose Estimation using Deep Learning. Issue 21 (2019) - Jeon, MyungHwan; Lee, Yeongjun; Shin, Young-Sik; Jang, Hyesu; Kim, Ayoung
Abstract: 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.