This leaderbord shows the ranking for Model-based 2D detection of seen objects on LM-O. 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) | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2023-09-25 | GDet2023 | RGB | 0.707 | 0.939 | 0.833 | 0.516 | 0.741 | 0.748 | 0.746 | 0.764 | 0.770 | 0.546 | 0.797 | 0.776 | 0.228 | |
2023-09-27 | GDet2023-PBR | RGB | 0.707 | 0.939 | 0.833 | 0.516 | 0.741 | 0.748 | 0.746 | 0.764 | 0.770 | 0.546 | 0.797 | 0.776 | 0.228 | |
2022-10-16 | DLZDet-PBR1 (DLZDet-PBR1) | RGB | 0.706 | 0.942 | 0.838 | 0.519 | 0.742 | 0.745 | 0.750 | 0.783 | 0.790 | 0.558 | 0.820 | 0.813 | -1.000 | |
2022-10-16 | DLZDet-PBR+Real (DLZDet-PBR+Real) | RGB | 0.706 | 0.942 | 0.838 | 0.519 | 0.742 | 0.745 | 0.750 | 0.783 | 0.790 | 0.558 | 0.820 | 0.813 | -1.000 | |
2022-10-14 | GDRNPPDet_PBR | RGB | 0.695 | 0.948 | 0.827 | 0.500 | 0.731 | 0.731 | 0.734 | 0.752 | 0.759 | 0.531 | 0.788 | 0.765 | 0.082 | |
2022-10-14 | GDRNPPDet_PBRReal | RGB | 0.695 | 0.948 | 0.827 | 0.500 | 0.731 | 0.731 | 0.734 | 0.752 | 0.759 | 0.531 | 0.788 | 0.765 | 0.082 | |
2022-07-21 | Extended FCOS-PBR (v2) | RGB | 0.675 | 0.942 | 0.807 | 0.428 | 0.719 | 0.785 | 0.707 | 0.728 | 0.731 | 0.446 | 0.771 | 0.816 | -1.000 | |
2022-07-23 | Extended FCOS-MixPBR (v2) | RGB | 0.675 | 0.942 | 0.807 | 0.428 | 0.719 | 0.785 | 0.707 | 0.728 | 0.731 | 0.446 | 0.771 | 0.816 | 0.030 | |
2022-05-04 | CosyPose-ECCV20-PBR-1VIEW | RGB | 0.566 | 0.872 | 0.647 | 0.114 | 0.624 | 0.552 | 0.603 | 0.613 | 0.613 | 0.284 | 0.669 | 0.599 | 0.053 | |
2022-05-04 | CosyPose-ECCV20-SYNT+REAL-1VIEW | RGB | 0.566 | 0.872 | 0.647 | 0.114 | 0.624 | 0.552 | 0.603 | 0.613 | 0.613 | 0.284 | 0.669 | 0.599 | 0.053 |
Tip: Hover over the numbers to see more decimal places.