3 accepted papers
In this work we address the problem of 3D object detection from point clouds in data-limited environments. Training with simulated data is a common approach in such scenarios; however a sim-to-real gap exists between clean and crisp simulated clouds and noisy real clouds. Previous sim-to-real approa
In this work we address the challenge of predicting the missing dimension (elevation angle) from 2D underwater sonar images. The high noise levels in these images, from phenomena such as non-diffuse reflections, frequently limits the usefulness of physical models. We thus propose the utilization of…
In this work we develop a novel framework that enables the real-time 3D reconstruction of underwater environments using features from 2D sonar images. Due to noisy and low-resolution imagery as compared with standard cameras, automatic feature extractors for sonar images are not reliable in many sce…