notesum.ai
Published at December 9On-Device Self-Supervised Learning of Low-Latency Monocular Depth from Only Events
cs.RO
cs.CV
Released Date: December 9, 2024
Authors: Jesse Hagenaars, Yilun Wu1, Federico Paredes-Vallés, Stein Stroobants1, Guido de Croon
Aff.: 1TU Delft

| outdoor_day1 | outdoor_night1 | |||||
|---|---|---|---|---|---|---|
| Depth Cutoff | 10m | 20m | 30m | 10m | 20m | 30m |
| Zhu et al. [39] 333The network uses events as input but was trained with intensity frames in the loss function. Therefore, it is included as a reference but is not directly comparable to self-supervised methods trained solely on event data. | 1.40 | 2.07 | 2.65 | 2.18 | 2.70 | 3.64 |
| Zhu et al. [39] | 3.90 | 3.79 | 4.89 | 5.55 | 4.57 | 5.72 |
| Zhu et al. [38] | 2.72 | 3.84 | 4.40 | 3.13 | 4.02 | 4.89 |
| Ours | 2.25 | 3.36 | 4.23 | 3.25 | 3.83 | 4.50 |
| \hdashlineOurs (Dense) | 1.96 | 2.67 | 3.29 | 2.92 | 3.56 | 4.28 |