Research map / Learning theory and algorithms / Matrix and tensor methods
Consensus Maximization With Linear Matrix Inequality Constraints
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add LMI constraints to the consensus search | Similarity Transformation optimization · Synthetic data, increasing outlier rates | runtime: 0.26 vs 0.61; 0.62 vs 9; 1.24 vs 48; 2.30 vs 498 | Helped |
| Add LMI constraints to the consensus search | Similarity Transformation optimization · Synthetic data, N=40 and N=50 | runtime: 0.44 vs 2; 1.17 vs 47; 2.68 vs 467; 0.64 vs 7; 2.05 vs 315 | Helped |
| Add a rotation angle constraint (ablation) | Absolute Pose optimization · Real data, Exp01 | runtime: 13.86 -> 2.96 | Helped |
| Add a rotation angle constraint (ablation) | Absolute Pose optimization · Real data, Exp02 | runtime: 25.71 -> 2.78 | Helped |
| Add a rotation angle constraint (ablation) | Absolute Pose optimization · Real data, Exp03 | runtime: 50.27 -> 13.80 | Helped |
| Add a rotation angle constraint (ablation) | Absolute Pose optimization · Real data, Exp04 | runtime: 61.18 -> 20.44 | Helped |
| Add a rotation angle constraint (ablation) | Absolute Pose optimization · Real data, Exp05 | runtime: 174.81 -> 10.40 | Helped |
| Add a rotation angle constraint (ablation) | Absolute Pose optimization · Real data, Exp06 | runtime: 120.24 -> 58.06 | Helped |
| Use the global LMI-constrained method instead of RANSAC | Relative Pose estimation · Fountain real data | inliers: 20 / 39 -> 25 / 39 | Helped |
| Use the global LMI-constrained method instead of RANSAC | Relative Pose estimation · Herz-Jesu real data | inliers: 35 / 70 -> 49 / 70 | Helped |
Closest papers by meaning
- An Exact Penalty Method for Locally Convergent Maximum Consensus (CVPR 2017 · similarity 0.88)
- Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery (ICML 2025 · similarity 0.84)
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- A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion (CVPR 2024 · similarity 0.84)
- LERE: Learning-Based Low-Rank Matrix Recovery with Rank Estimation (AAAI 2024 · similarity 0.83)
- Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing (NeurIPS 2024 · similarity 0.83)
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