Paper · ≈ 1 min read
DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras
Outgoing relations
- addresses → Visual SLAM (ResearchTopic)
- implemented_in → About princeton-vl/DROID-SLAM (Repository)
- introduces → DROID-SLAM (Algorithm)
- part_of → 3D/4D Vision and Reconstruction (ResearchField)
- uses_metric → Accuracy (Metric)
- uses_metric → LPIPS (Metric)
- uses_metric → PSNR (Metric)
- uses_metric → SSIM (Metric)
Incoming relations
- mentioned_in → About princeton-vl/DROID-SLAM (Repository)
Connected node types
- Metric: 4
- Repository: 2
- Algorithm: 1
- ResearchField: 1
- ResearchTopic: 1
Mentions in the corpus
- part_of Evidence: --- type: Paper arxiv: "2108.10869" arxiv_url: https://arxiv.org/abs/21…
- mentioned_in Claim: --- type: Paper arxiv: "2108.10869" arxiv_url: https://arxiv.org/abs/2108.10869 title: "DROID-S…
- part_of Evidence: We introduce DROID-SLAM, a new deep learning based SLAM system.
- part_of Evidence: Despite training on monocular video, it can leverage stereo or RGB-D vi…
- part_of Evidence: The system is trained end-to-end on monocular video but, at test time,…
- mentioned_in About princeton-vl/DROID-SLAM
- summarizes Project Pulse
- synthesizes Topic — Visual SLAM
- summarizes Topic — Visual SLAM
- summarizes Field Overview — 3D/4D Vision and Reconstruction
Cross-references in raw data
Source provenance
examples/demo-corpus/data/research/papers/arxiv-2108-10869/abstract.md