Papers › Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps
Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps
Kieran Saunders, George Vogiatzis, Luis J. Manso
Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture complexity. This paper shows that state-of-the-art performance can also be achieved by improving the learning process rather than increasing model complexity. More specifically, we propose (i) disregarding small potentially dynamic objects when training, and (ii) employing an appearance-based approach to separately estimate object pose for truly dynamic objects. We demonstrate that these simplifications reduce GPU memory usage by 29% and result in qualitatively and quantitatively improved depth maps. The code is available at https://github.com/kieran514/Dyna-DM.
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Tasks
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | Delta < 1.25 | 0.871 | #52 of 55 | Archive leaderboard | report |
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | Delta < 1.25^2 | 0.959 | #52 of 55 | Archive leaderboard | report |
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | Delta < 1.25^3 | 0.982 | #52 of 55 | Archive leaderboard | report |
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | RMSE | 4.698 | #52 of 55 | Archive leaderboard | report |
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | RMSE log | 0.192 | #52 of 55 | Archive leaderboard | report |
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | Sq Rel | 0.785 | #52 of 55 | Archive leaderboard | report |
| Monocular Depth Estimation | KITTI Eigen split unsupervised | Dyna-DM | absolute relative error | 0.115 | #52 of 55 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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