Research map / Learning theory and algorithms / Combinatorial and search optimization
Efficient Solvers for Minimal Problems by Syzygy-Based Reduction
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use syzygy-based reduction to form the elimination template | Automatic polynomial solver generator · Minimal problems in geometric computer vision | template size: 411 × 489 -> 40 × 57 | Helped |
| Use syzygy-based reduction | Automatic polynomial solver generator · TDOA offset rank 3, 6,8 pts | template size: 1359 × 754 -> 356 × 345 | Helped |
| Use syzygy-based reduction | Automatic polynomial solver generator · Dual-Receiver TDOA 5pt | template size: 2, 625 × 2, 352 -> 455 × 768 | Helped |
| Use syzygy-based reduction | Automatic polynomial solver generator · Optimal PnP | template size: 120 × 120 -> 88 × 115 | Helped |
| Use syzygy-based reduction | Automatic polynomial solver generator · Stitching + constant focal length + radial distortion, 3pt | template size: 54 × 77 -> 48 × 66 | Helped |
| Use non-unit quaternions for the rotation-only stage (ablation) | Three-view solver with known rotation axis · One point and two lines | runtime: 1, 306 × 1, 261; 0.57s -> 12 × 20; 0.3ms | Helped |
| Eliminate translations using the point depths (ablation) | Three-view solver with known rotation axis · One point and two lines | template size: 1, 306 × 1, 261 -> 652 × 462 | Helped |
| Use non-unit rather than unit quaternions (ablation) | Three-view solver with known rotation axis · One point and two lines | template size: 96 × 88 -> 12 × 20 | Helped |
| Partially reduce the template using combinations of four equations (ablation) | Nine-lines solver · Nine lines in three views | template size: 20, 273 × 14, 281 -> 16, 278 × 13, 735 | Helped |
| Use syzygy-based reduction | Automatic polynomial solver generator · Minimal problems in geometric computer vision | template size: Table 1 | Mixed |
Closest papers by meaning
- A Sparse Resultant Based Method for Efficient Minimal Solvers (CVPR 2020 · similarity 0.87)
- Simulator HC: Regression-based Online Simulation of Starting Problem-Solution Pairs for Homotopy Continuation in Geometric Vision (CVPR 2025 · similarity 0.84)
- Learning Polynomial Problems with $SL(2, \mathbb{R})$-Equivariance (ICLR 2024 · similarity 0.82)
- Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics (ICML 2025 · similarity 0.81)
- Learning to compute Gröbner bases (NeurIPS 2024 · similarity 0.81)
- Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms (NeurIPS 2025 · similarity 0.80)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
