Model-based 2D detection of unseen objects – TUD-L

This leaderbord shows the ranking for Model-based 2D detection of unseen objects on TUD-L. The reported time is the average time to generate predictions for all objects in a single image (averaged over the datasets).

Date (UTC) Submission Test image AP AP50 AP75 APS APM APL AR1 AR10 AR100 ARS ARM ARL Time (s)
2024-11-16 MUSE (full) RGB 0.595 0.878 0.728 0.096 0.609 0.659 0.674 0.698 0.698 0.500 0.686 0.777 0.622
2025-03-07 anonymity (.) RGB 0.593 0.876 0.723 0.201 0.607 0.636 0.672 0.697 0.697 0.500 0.684 0.775 0.562
2023-12-05 SAM6D-FastSAM RGB-D 0.573 0.865 0.672 0.577 0.583 0.621 0.648 0.667 0.667 0.600 0.662 0.718 0.333
2024-09-18 F3DT2D (test01/blenderproc) RGB 0.573 0.856 0.696 0.026 0.573 0.700 0.660 0.689 0.689 0.475 0.676 0.782 0.449
2024-03-22 SAM6D-FastSAM(RGB) RGB 0.546 0.830 0.633 0.536 0.554 0.608 0.631 0.658 0.658 0.575 0.655 0.712 0.186
2023-12-05 SAM6D RGB-D 0.537 0.850 0.617 0.575 0.549 0.446 0.634 0.655 0.659 0.700 0.652 0.605 2.393
2023-08-02 CNOS (FastSAM) (FastSAM) RGB 0.534 0.829 0.623 0.507 0.553 0.378 0.635 0.655 0.655 0.675 0.652 0.603 0.163
2023-11-23 ViewInvDet RGB 0.508 0.813 0.584 0.599 0.533 0.436 0.620 0.648 0.648 0.650 0.649 0.633 1.268
2024-05-08 NIDS-Net_WA_Sappe RGB 0.486 0.829 0.522 0.363 0.525 0.414 0.584 0.598 0.598 0.475 0.592 0.595 0.489
2024-05-08 NIDS-Net_WA RGB 0.460 0.807 0.481 0.316 0.507 0.288 0.567 0.581 0.581 0.475 0.574 0.521 0.485
2024-05-08 NIDS-Net_basic RGB 0.434 0.775 0.462 0.047 0.474 0.309 0.554 0.577 0.577 0.475 0.573 0.501 0.487
2023-09-17 ZeroPose RGB 0.431 0.650 0.514 0.030 0.442 0.446 0.540 0.607 0.614 0.775 0.611 0.510 3.406
2023-08-02 CNOS (SAM) (SAM) RGB 0.368 0.598 0.399 0.308 0.383 0.245 0.453 0.476 0.476 0.675 0.477 0.420 1.623

Tip: Hover over the numbers to see more decimal places.

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