Paper · ≈ 1 min read
GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting
Outgoing relations
- addresses → Visual SLAM (ResearchTopic)
- belongs_to_approach_family → Gaussian Splatting Reconstruction (ApproachFamily)
- evaluated_on → Replica (Benchmark)
- part_of → 3D/4D Vision and Reconstruction (ResearchField)
- uses → Gaussian Splatting (MethodologicalConcept)
- uses_metric → Accuracy (Metric)
- uses_metric → LPIPS (Metric)
- uses_metric → PSNR (Metric)
- uses_metric → SSIM (Metric)
- uses_metric → mAP (Metric)
Connected node types
- Metric: 5
- ApproachFamily: 1
- Benchmark: 1
- MethodologicalConcept: 1
- ResearchField: 1
- ResearchTopic: 1
Mentions in the corpus
- part_of Evidence: --- type: Paper arxiv: "2311.11700" arxiv_url: https://arxiv.org/abs/23…
- mentioned_in Claim: --- type: Paper arxiv: "2311.11700" arxiv_url: https://arxiv.org/abs/2311.11700 title: "GS-SLAM…
- part_of Evidence: In this paper, we introduce \textbf{GS-SLAM} that first utilizes 3D Gau…
- part_of Evidence: Specifically, we propose an adaptive expansion strategy that adds new o…
- part_of Evidence: Compared to recent SLAM methods employing neural implicit representatio…
- part_of Evidence: Our method achieves competitive performance compared with existing stat…
- part_of Evidence: It facilitates a better balance between efficiency and accuracy.
- part_of Evidence: On Replica and TUM-RGBD, GS-SLAM achieves competitive tracking accuracy…
- summarizes Project Pulse
- synthesizes Topic — Gaussian Splatting Reconstruction
- summarizes Topic — Gaussian Splatting Reconstruction
- synthesizes Topic — Visual SLAM
- summarizes Topic — Visual SLAM
- synthesizes Comparison — Dynamic Gaussian Splatting vs Gaussian Splatting Reconstruction
- summarizes Comparison — Dynamic Gaussian Splatting vs Gaussian Splatting Reconstruction
- summarizes Field Overview — 3D/4D Vision and Reconstruction
Cross-references in raw data
Source provenance
examples/demo-corpus/data/research/papers/arxiv-2311-11700/abstract.md