Leaderboard
Calibration methods ranked across sensor configurations and algorithm families. Each entry reports reprojection error, extrinsic accuracy against the Open MVIS consensus baseline, time-offset error, runtime, and convergence rate — with mean ± stddev over N runs where the submitter provided them.
5 entries
| Method | Family | Sensor config | Dataset | Reproj. (px) | Rot err (deg) | Trans err (cm) | Time offs. (ms) | Runtime (s) | Conv. (%) | Links |
|---|---|---|---|---|---|---|---|---|---|---|
| Basalt vmaster | B-spline | 1 IMU + 1 cam 1 IMU · 1 cam | open_mvis_4imu3cam v1.0 | 0.49 | 0.12 | 0.22 | 12.5 | 58 | 90 | 💾 📄 |
| CamCalib v0.4.2 | Factor graph | Multi IMU + multi cams 4 IMU · 4 cam | open_mvis_4imu4cam v1.0 | 0.41 ± 0.03 | 0.08 ± 0.02 | 0.12 ± 0.04 | 0.31 ± 0.05 | 142 ± 8 | 100 | 💾 |
| Kalibr v1.0 | B-spline | 1 IMU + 1 cam 1 IMU · 1 cam | open_mvis_4imu3cam v1.0 | 0.52 | 0.15 | 0.28 | 0.04 | 420 | 100 | 💾 📄 |
| MVIS v1.0 | Factor graph | Multi IMU + multi cams 4 IMU · 3 cam | open_mvis_4imu3cam v1.0 | 0.38 ± 0.04 | 0.07 ± 0.02 | 0.1 ± 0.03 | 0.28 ± 0.04 | 178 ± 12 | 100 | 💾 |
| OpenVINS v2.6 | EKF | 1 IMU + 1 cam 1 IMU · 1 cam | open_mvis_4imu3cam v1.0 | 0.61 | 0.18 | 0.34 | 0.45 | 38 | 95 | 💾 📄 |
Filter state is preserved in the URL, so a specific comparison can be cited
directly — for example
/benchmark/leaderboard/?config=multi_imu_multi_cam&sort=timeoffset_err_ms.
Reading the table
Section titled “Reading the table”- Lower is better for every error metric; higher is better for convergence rate.
—means not reported, not zero. Absence is shown rather than filled in.- Compare within a sensor configuration, not across. A single-IMU single-camera result and a four-IMU result are different problems.
How the categories are defined, how scores are computed, and what the baseline is: Methodology.
Submit
Section titled “Submit”Add your method with a pull request — one YAML file, schema-validated in CI. See Submit results.