DASH-SLAM: Calibration-Free Metric Monocular SLAM via Depth Scale Propagation
Overview
This paper introduces DASH-SLAM, a monocular Simultaneous Localization and Mapping (SLAM) system that integrates metric depth predictions from the pretrained Depth Anything 3 model into a shared-keyframe pose graph without requiring task-specific fine-tuning.
Generated from attributed reports · Updated 13 hours ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
No current evidence-backed claims. Missing information remains not reported.
Report timeline
Follow attributed reports and material updates.
- arXiv Robotics — research abstractsSignalDASH-SLAM: Calibration-Free Metric Monocular SLAM via Depth Scale Propagation
This paper introduces DASH-SLAM, a monocular Simultaneous Localization and Mapping (SLAM) system that integrates metric depth predictions from the pretrained Depth Anything 3 model into a shared-keyframe pose graph without requiring task-specific fine-tuning.
Event coverage history
There is not enough continuous observation data to show a trend.
Timezone · UTC
Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).