Neural networks estimate depth distributions from event camera data using six input representations and three uncertainty models, with 10-bin log-normal and 5-bin evidential variants performing best on synthetic-to-real transfer.
Blinkvision: A benchmark for optical flow, scene flow and point tracking estimation using rgb frames and events
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
dataset 1
citation-polarity summary
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1roles
dataset 1polarities
use dataset 1representative citing papers
citing papers explorer
-
Neuromorphic Monocular Depth Estimation with Uncertainty Modeling
Neural networks estimate depth distributions from event camera data using six input representations and three uncertainty models, with 10-bin log-normal and 5-bin evidential variants performing best on synthetic-to-real transfer.