This leaderbord shows the ranking for Model-based 2D detection of unseen objects on HB. The metrics are defined in Section 2 of the BOP 2022 paper. The reported time is the average image processing time.
Date (UTC) | Submission | Test image | AP | AP50 | AP75 | APS | APM | APL | AR1 | AR10 | AR100 | ARS | ARM | ARL | Time (s) | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-05-08 | NIDS-Net_WA | RGB | 0.594 | 0.764 | 0.618 | 0.045 | 0.606 | 0.643 | 0.643 | 0.650 | 0.650 | 0.046 | 0.648 | 0.802 | 0.467 | |
2024-05-08 | NIDS-Net_WA_Sappe | RGB | 0.587 | 0.755 | 0.609 | 0.044 | 0.598 | 0.665 | 0.634 | 0.649 | 0.649 | 0.046 | 0.645 | 0.850 | 0.463 | |
2024-09-18 | F3DT2D (test01/blenderproc) | RGB | 0.577 | 0.721 | 0.610 | 0.006 | 0.586 | 0.737 | 0.614 | 0.626 | 0.626 | 0.017 | 0.624 | 0.846 | 0.456 | |
2023-11-23 | ViewInvDet | RGB | 0.554 | 0.721 | 0.581 | 0.001 | 0.560 | 0.685 | 0.616 | 0.624 | 0.624 | 0.017 | 0.621 | 0.816 | 1.719 | |
2023-12-05 | SAM6D-FastSAM | RGB-D | 0.551 | 0.707 | 0.573 | 0.018 | 0.556 | 0.727 | 0.590 | 0.595 | 0.595 | 0.017 | 0.590 | 0.826 | 0.442 | |
2024-05-08 | NIDS-Net_basic | RGB | 0.548 | 0.700 | 0.570 | 0.044 | 0.558 | 0.629 | 0.598 | 0.613 | 0.613 | 0.046 | 0.609 | 0.832 | 0.469 | |
2023-12-05 | SAM6D | RGB-D | 0.530 | 0.722 | 0.549 | 0.006 | 0.541 | 0.601 | 0.575 | 0.582 | 0.582 | 0.043 | 0.580 | 0.711 | 2.957 | |
2024-03-22 | SAM6D-FastSAM(RGB) | RGB | 0.523 | 0.676 | 0.544 | 0.018 | 0.525 | 0.680 | 0.577 | 0.585 | 0.585 | 0.017 | 0.578 | 0.822 | 0.249 | |
2023-08-02 | CNOS (FastSAM) (FastSAM) | RGB | 0.517 | 0.669 | 0.532 | 0.006 | 0.523 | 0.658 | 0.578 | 0.586 | 0.586 | 0.017 | 0.579 | 0.826 | 0.220 | |
2023-08-02 | CNOS (SAM) (SAM) | RGB | 0.423 | 0.565 | 0.440 | 0.005 | 0.435 | 0.386 | 0.475 | 0.479 | 0.479 | 0.043 | 0.477 | 0.522 | 1.803 | |
2023-09-17 | ZeroPose | RGB | 0.398 | 0.547 | 0.397 | 0.000 | 0.419 | 0.431 | 0.492 | 0.525 | 0.525 | 0.003 | 0.531 | 0.638 | 3.628 |
Tip: Hover over the numbers to see more decimal places.