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MGS-SLAM: Monocular Sparse Tracking and Gaussian Mapping with Depth Smooth Regularization
To address these limitations, we uniquely integrates advanced sparse visual odometry with a dense Gaussian Splatting scene representation for the first time, thereby eliminating the dependency on depth maps typical of Gaussian Splatting-based SLAM systems and enhancing tracking robustness.
Data-driven sparse polynomial chaos expansion for models with dependent inputs
Recently, different approaches have been proposed for models with dependent inputs to expand the use of PCEs to more real-world applications.
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