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.
InAdvances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024
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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.