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Found 8 papers, 4 papers with code
Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets
In anomaly detection, a prominent task is to induce a model to identify anomalies learned solely based on normal data.
Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction
We present Gradient-SDF, a novel representation for 3D geometry that combines the advantages of implict and explicit representations.
Square Root Marginalization for Sliding-Window Bundle Adjustment
The square root formulation pervades three major aspects of our optimization-based sliding-window estimator: for bundle adjustment we eliminate landmark variables with nullspace projection; to store the marginalization prior we employ a matrix square root of the Hessian; and when marginalizing old poses we avoid forming normal equations and update the square root prior directly with a specialized QR decomposition.
Efficient Derivative Computation for Cumulative B-Splines on Lie Groups
Continuous-time trajectory representation has recently gained popularity for tasks where the fusion of high-frame-rate sensors and multiple unsynchronized devices is required.
Rolling-Shutter Modelling for Direct Visual-Inertial Odometry
The visual part of the system performs a photometric bundle adjustment on a sparse set of points.
Visual-Inertial Mapping with Non-Linear Factor Recovery
We reconstruct a set of non-linear factors that make an optimal approximation of the information on the trajectory accumulated by VIO.
Direct Sparse Odometry with Rolling Shutter
Neglecting the effects of rolling-shutter cameras for visual odometry (VO) severely degrades accuracy and robustness.
The TUM VI Benchmark for Evaluating Visual-Inertial Odometry
For trajectory evaluation, we also provide accurate pose ground truth from a motion capture system at high frequency (120 Hz) at the start and end of the sequences which we accurately aligned with the camera and IMU measurements.
