A reliability-prediction network and gated fusion method are used to filter glare-corrupted depth data before it enters robot navigation costmaps, demonstrated on a RealSense-equipped mobile platform.
Seeing and seeing through the glass: Real and synthetic data for multi-layer depth estimation
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Reliability modeling of depth measurements enables glare-resilient occupancy grid costmaps for mobile robots.
citing papers explorer
-
Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps
A reliability-prediction network and gated fusion method are used to filter glare-corrupted depth data before it enters robot navigation costmaps, demonstrated on a RealSense-equipped mobile platform.
-
Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps
Reliability modeling of depth measurements enables glare-resilient occupancy grid costmaps for mobile robots.