Published in ICCV, 2023
Our work makes self-supervised monocular depth estimation much more robust to changes in weather, time of day and image degradation.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://kieran514.github.io/files/Robust-Depth.pdf
Published in ICARSC, 2023
We aim to find truly dynamic objects in a scene to improve self-supervised monocular depth estimation.
Recommended citation: K. Saunders, G. Vogiatzis and L. J. Manso, "Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps," 2023 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Tomar, Portugal, 2023, pp. 10-16, doi: 10.1109/ICARSC58346.2023.10129564. https://kieran514.github.io/files/Dyna-DM.pdf