DL-SLAM uses dual-level (pixel and object) dynamic probabilities from semantic-geometric fusion to produce artifact-free static maps and up to 13% better tracking accuracy in dynamic scenes.
Oswald, and Marc Pollefeys
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DL-SLAM: Enabling High-Fidelity Gaussian Splatting SLAM in Dynamic Environments based on Dual-Level Probability
DL-SLAM uses dual-level (pixel and object) dynamic probabilities from semantic-geometric fusion to produce artifact-free static maps and up to 13% better tracking accuracy in dynamic scenes.