BOP: Benchmark for 6D Object Pose Estimation

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 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	AP_S	AP_M	AP_L	AR₁	AR₁₀	AR₁₀₀	AR_S	AR_M	AR_L	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
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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