Motion Forecasting On Argoverse Cvpr 2020

Metriken

DAC (K=6)

MR (K=1)

MR (K=6)

brier-minFDE (K=6)

minADE (K=1)

minADE (K=6)

minFDE (K=1)

minFDE (K=6)

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Vergleichstabelle

Modellname	DAC (K=6)	MR (K=1)	MR (K=6)	brier-minFDE (K=6)	minADE (K=1)	minADE (K=6)	minFDE (K=1)	minFDE (K=6)
Modell 1	0.9831	0.5933	0.1674	2.0999	1.7176	0.8853	3.7966	1.4055
tenet-transformer-encoding-network-for	0.9863	0.5596	0.1272	1.7667	1.6565	0.8121	3.6081	1.2141
Modell 3	0.9263	0.7498	0.7498	4.9209	2.1686	2.1686	4.9209	4.9209
Modell 4	0.8857	0.8348	0.8348	7.8875	3.5333	3.5333	7.8875	7.8875
Modell 5	0.9183	0.7352	0.5901	4.0999	2.3865	1.6055	5.488	3.4055
Modell 6	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 7	0.9877	0.5791	0.1432	1.9162	1.6856	0.8186	3.7588	1.2754
Modell 8	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7642	1.355
Modell 9	0.9838	0.5701	0.1438	1.8752	1.6242	0.8331	3.58	1.2748
Modell 10	0.9124	0.8774	0.5504	4.1457	3.467	1.7875	7.4546	3.4512
Modell 11	0.9856	0.7161	0.1589	2.1082	2.2709	0.9583	5.0216	1.4138
Modell 12	0.9738	0.6685	0.6685	4.0972	1.8312	1.8312	4.0972	4.0972
Modell 13	0.9874	0.5598	0.1306	1.78	1.6244	0.81	3.5572	1.1996
Modell 14	0.9887	0.6467	0.1676	2.3613	1.9108	0.99	4.2597	1.6668
Modell 15	0.9671	0.8355	0.4889	4.1988	3.6495	1.888	8.1197	3.5044
Modell 16	0.9826	0.669	0.1849	2.083	2.0363	0.9105	4.5807	1.4341
Modell 17	0.9843	0.5665	0.1474	1.954	1.6217	0.8294	3.5508	1.2595
Modell 18	0.9759	0.6795	0.6795	4.1704	1.8705	1.8705	4.1704	4.1704
Modell 19	0.9871	0.5877	0.1434	1.9922	1.7368	0.8948	3.7874	1.2978
leveraging-future-relationship-reasoning-for	0.9878	0.5728	0.143	1.9365	1.7063	0.8165	3.7486	1.2671
Modell 21	0.9912	0.5918	0.205	2.3544	1.8594	1.1463	3.8216	1.7597
home-heatmap-output-for-future-motion	0.983	0.5723	0.0846	1.8601	1.6986	0.8904	3.681	1.2919
Modell 23	0.8441	0.8868	0.8868	8.7522	3.9771	3.9771	8.7522	8.7522
Modell 24	0.9185	0.7668	0.7668	5.7168	2.1875	2.1875	5.0224	5.0224
Modell 25	0.9691	0.6825	0.6825	4.2673	1.9123	1.9123	4.2673	4.2673
Modell 26	0.7042	0.9967	0.9893	26.4057	30.7524	28.3813	31.1513	25.7113
Modell 27	0.9882	0.5401	0.1223	1.8095	1.5097	0.7543	3.3621	1.1376
Modell 28	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 29	0.9883	0.5555	0.1297	1.8738	1.6266	0.7863	3.5825	1.1974
Modell 30	0.9835	0.6019	0.1586	2.044	1.7453	0.8642	3.8981	1.3496
Modell 31	0.9922	0.5154	0.1032	1.6820	1.4412	0.7282	3.1777	1.0566
Modell 32	0.9799	0.6036	0.1764	2.0408	1.73	0.8621	3.8782	1.4071
Modell 33	0.9848	0.6354	0.1677	2.0884	1.89	0.8888	4.2265	1.401
Modell 34	0.9829	0.5871	0.1471	1.9006	1.6864	0.8406	3.7477	1.2785
Modell 35	0.9854	0.6122	0.1692	2.1486	1.7343	0.8963	3.8532	1.4542
lanercnn-distributed-representations-for	0.9903	0.5685	0.1232	2.147	1.6852	0.9038	3.6916	1.4526
Modell 37	0.9931	0.5348	0.5348	3.2923	1.5407	1.5407	3.2923	3.2923
Modell 38	0.9835	0.5756	0.5756	3.5154	1.5969	1.5969	3.5154	3.5154
Modell 39	0.9875	0.6749	0.2585	2.8266	2.0414	1.1518	4.6325	2.1322
Modell 40	0.9834	0.6241	0.6241	3.9973	1.809	1.809	3.9973	3.9973
Modell 41	0.755	0.9851	0.9817	23.394	12.3146	11.8296	23.7276	22.6995
r-pred-two-stage-motion-prediction-via-tube	0.992	0.5344	0.1165	1.7765	1.5843	0.7629	3.4718	1.1236
Modell 43	0.9898	0.5867	0.115	2.0978	1.9105	1.2187	3.8217	1.5582
Modell 44	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 45	0.9892	0.5754	0.1303	1.8584	1.6788	0.8194	3.7087	1.2186
Modell 46	0.9514	0.7892	0.4141	3.5654	2.9029	1.4811	6.8301	2.871
Modell 47	0.1475	1.0	0.8261	6.3362	38.9455	3.541	57.7046	5.6417
Modell 48	0.9118	0.8087	0.8087	5.8239	2.5344	2.5344	5.8239	5.8239
Modell 49	0.9817	0.5827	0.1651	2.0651	1.6666	0.866	3.6886	1.3707
multi-modal-motion-prediction-with	0.9852	0.6023	0.1429	1.9393	1.735	0.8372	3.9007	1.2905
Modell 51	0.9812	0.6321	0.1791	2.0798	1.8436	0.9013	4.0875	1.4384
Modell 52	0.8934	0.7861	0.3389	2.7277	2.5904	1.1394	5.7132	2.0333
Modell 53	0.9849	0.6272	0.1591	2.006	1.8103	0.8703	3.9733	1.3505
Modell 54	0.9893	0.5435	0.1163	1.7963	1.5099	0.7797	3.3297	1.1675
Modell 55	0.9824	0.5966	0.1666	2.0714	1.7168	0.8702	3.8171	1.377
Modell 56	0.8697	0.8449	0.8449	8.3792	3.3726	3.3726	7.7392	7.7392
wayformer-motion-forecasting-via-simple	0.9893	0.5716	0.1186	1.7408	1.636	0.7676	3.6559	1.1616
Modell 58	0.9864	0.5634	0.1408	1.9737	1.6262	0.8308	3.5851	1.2793
Modell 59	0.9485	0.7601	0.678	4.9666	3.0107	2.0839	6.688	4.2735
Modell 60	0.964	0.8355	0.5821	4.7203	3.6495	2.0775	8.1197	4.0258
Modell 61	0.9812	0.5926	0.1647	1.9981	1.7163	0.8809	3.801	1.3845
Modell 62	0.9866	0.5565	0.1427	1.9744	1.5851	0.8444	3.4838	1.28
Modell 63	0.9851	0.6277	0.195	2.5316	1.9152	1.0783	4.194	1.8371
prank-motion-prediction-based-on-ranking	0.9891	0.5955	0.5955	3.8239	1.7284	1.7284	3.8239	3.8239
Modell 65	0.9847	0.5764	0.1395	1.8988	1.645	0.8277	3.6029	1.2532
Modell 66	0.9437	0.7964	0.4199	3.8051	2.5911	1.8703	5.6038	3.1107
thomas-trajectory-heatmap-output-with-learned-1	0.9781	0.5613	0.1038	1.9736	1.6686	0.9423	3.593	1.4388
Modell 68	0.9568	0.7171	0.5363	4.2643	2.4032	1.6939	5.4621	3.5698
Modell 69	0.9909	0.553	0.1209	1.8188	1.6287	0.818	3.5263	1.1888
Modell 70	0.9825	0.6333	0.1732	2.2004	1.8785	0.9172	4.2259	1.506
Modell 71	0.9842	0.6178	0.154	2.0328	1.7737	0.8436	4.0033	1.3383
Modell 72	0.4323	0.9936	0.9312	24.3515	17.0122	12.6584	34.3376	23.657
Modell 73	0.9192	0.7773	0.7773	5.1247	2.2181	2.2181	5.1247	5.1247
Modell 74	0.9179	0.6576	0.5428	3.7921	1.9103	1.5031	4.2923	3.0976
Modell 75	0.9521	0.943	0.3539	2.8102	4.9745	1.2216	10.0298	2.1157
trajectory-forecasting-on-temporal-graphs	0.9837	0.5984	0.1528	1.9285	1.7716	0.8607	3.9031	1.3055
Modell 77	0.4222	0.6517	0.3579	2.994	2.3896	1.8694	4.1008	2.2995
Modell 78	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 79	0.3525	0.737	0.6583	5.0426	22.3728	2.1476	25.4924	4.7166
Modell 80	0.9742	0.9083	0.5156	4.8253	5.5699	2.2968	11.0515	4.1309
Modell 81	0.9865	0.7452	0.1589	2.048	2.1902	0.848	4.915	1.3536
Modell 82	0.9776	0.7285	0.1951	2.1576	2.2283	0.9163	5.0944	1.4631
Modell 83	0.9815	0.6375	0.1865	2.0434	1.8637	0.8832	4.1511	1.4262
Modell 84	0.9876	0.718	0.3276	3.2327	2.4228	1.549	5.2943	2.5765
Modell 85	0.99	0.575	0.1266	1.8567	1.715	0.8285	3.7582	1.2403
Modell 86	0.9825	0.5981	0.1603	1.9863	1.7978	0.861	4.0415	1.3527
Modell 87	0.9891	0.5972	0.146	1.946	1.7338	0.8636	3.8476	1.3399
Modell 88	0.9816	0.5933	0.1217	2.1386	1.7995	0.9892	3.8357	1.5159
Modell 89	0.9875	0.5843	0.1258	1.9759	1.6791	0.8817	3.6321	1.2815
Modell 90	0.947	0.6688	0.3857	3.2277	1.9276	1.3568	4.2738	2.4881
Modell 91	0.9889	0.5862	0.148	1.9635	1.698	0.836	3.7395	1.2863
Modell 92	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 93	0.9877	0.6322	0.1707	2.1092	1.9536	0.8841	4.2854	1.4204
Modell 94	0.9848	0.6312	0.1635	2.0574	1.8397	0.8758	4.1061	1.3715
Modell 95	0.984	0.6151	0.1059	2.1898	1.8014	0.9779	3.9418	1.4953
Modell 96	0.9776	0.5968	0.1738	2.0975	1.731	0.8775	3.8592	1.4031
Modell 97	0.9888	0.5742	0.1327	1.9423	1.6492	0.8674	3.5879	1.2703
Modell 98	0.9805	0.6158	0.1666	2.0857	1.7762	0.8986	3.9079	1.3913
Modell 99	0.9839	0.6201	0.6201	3.9861	1.8062	1.8062	3.9861	3.9861
Modell 100	0.9044	0.8197	0.8197	6.1954	2.7291	2.7291	6.1954	6.1954
Modell 101	0.9408	0.8659	0.5203	3.8899	3.3858	1.684	7.6186	3.1954
Modell 102	0.9816	0.6329	0.1804	2.1001	1.9016	0.916	4.2119	1.4591
Modell 103	0.8878	0.8709	0.655	5.6308	3.4152	2.5705	7.2377	4.9364
ganet-goal-area-network-for-motion	0.9899	0.5499	0.1179	1.7899	1.5921	0.806	3.4548	1.1605
Modell 105	0.89	0.8602	0.8602	6.0771	2.7271	2.7271	6.0771	6.0771
Modell 106	0.9814	0.6353	0.1795	2.1037	1.8988	0.8943	4.2353	1.4645
Modell 107	0.9898	0.5814	0.1341	1.918	1.6561	0.8012	3.6496	1.2235
Modell 108	0.8654	0.9068	0.9068	6.992	3.2553	3.2553	6.992	6.992
Modell 109	0.2939	0.9999	0.8237	6.2931	32.9034	3.2331	46.7268	5.5987
Modell 110	0.9495	0.7756	0.3983	2.9967	2.7949	1.3502	6.0524	2.3501
Modell 111	0.9903	0.5579	0.121	1.8817	1.6117	0.813	3.5087	1.1873
Modell 112	0.9725	0.6344	0.2179	2.243	1.9044	0.9436	4.1917	1.5486
Modell 113	0.9769	0.6702	0.2129	2.1611	2.0401	0.9687	4.5299	1.5716
Modell 114	0.8697	0.889	0.889	6.7247	3.1088	3.1088	6.7247	6.7247
Modell 115	0.9826	0.6074	0.1619	2.0682	1.7365	0.8715	3.8482	1.3737
Modell 116	0.9699	0.7837	0.2189	2.3277	2.6392	0.9693	6.029	1.6332
Modell 117	0.9807	0.5852	0.1696	2.0993	1.6737	0.8858	3.6837	1.4049
Modell 118	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 119	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
holistic-transformer-a-joint-neural-network	0.9865	0.5496	0.1303	1.9172	1.5692	0.8123	3.4284	1.2227
multipath-efficient-information-fusion-and	0.9876	0.5645	0.1324	1.7932	1.6235	0.7897	3.6141	1.2144
Modell 122	0.9143	0.806	0.806	5.8185	2.5329	2.5329	5.8185	5.8185
Modell 123	0.9743	0.6879	0.3191	2.7237	2.0987	1.1624	4.6642	2.1036
Modell 124	0.832	0.9064	0.709	5.6071	5.8841	2.823	11.3051	4.9126
Modell 125	0.981	0.5962	0.1725	2.1136	1.7191	0.8883	3.8039	1.4192
Modell 126	0.7756	0.9238	0.9238	8.1441	3.9521	3.9521	8.1441	8.1441
Modell 127	0.9827	0.5875	0.1591	2.04	1.6883	0.862	3.7274	1.3456
Modell 128	0.9602	0.6278	0.214	2.2688	1.8335	0.9303	4.1274	1.5984
Modell 129	0.8983	0.8379	0.7805	6.0565	2.6883	2.4943	5.8451	5.362
Modell 130	0.991	0.7828	0.2904	3.2196	2.9576	1.4537	6.3673	2.5476
Modell 131	0.9718	0.8457	0.4903	3.7943	3.3035	1.6056	7.4299	3.0999
Modell 132	0.8857	0.8348	0.8348	7.8875	3.5333	3.5333	7.8875	7.8875
Modell 133	0.9865	0.7656	0.3969	3.1788	2.5888	1.4161	5.7465	2.4845
Modell 134	0.9808	0.6127	0.1779	2.4781	1.8312	1.0416	4.01	1.7936
Modell 135	0.9397	0.7411	0.3553	2.8147	2.2558	1.1807	5.1581	2.2379
Modell 136	0.958	0.802	0.3434	3.0901	3.0338	1.4024	7.0702	2.3957
Modell 137	0.9092	0.5887	0.1501	2.0058	11.3861	11.2834	3.7832	1.3114
Modell 138	0.9818	0.5889	0.1673	2.0717	1.7041	0.8663	3.7827	1.3772
Modell 139	0.951	0.6791	0.6791	4.5196	2.0031	2.0031	4.5196	4.5196
crat-pred-vehicle-trajectory-prediction-with	0.9558	0.6323	0.2624	2.5926	1.8162	1.0626	4.0576	1.8981
Modell 141	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 142	0.7734	0.8151	0.6899	5.3363	2.8257	2.1564	6.3946	4.6394
Modell 143	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 144	0.9886	0.5577	0.1351	1.9175	1.6453	0.7949	3.6269	1.2235
Modell 145	0.9584	0.7471	0.3393	3.2021	2.4611	1.2522	5.5965	2.5305
Modell 146	0.9494	0.7301	0.2845	2.8131	2.1057	1.1343	4.8259	2.1187
Modell 147	0.8857	0.8348	0.8348	7.8875	3.5333	3.5333	7.8875	7.8875
Modell 148	0.8857	0.8348	0.8348	7.8875	3.5333	3.5333	7.8875	7.8875
tpcn-temporal-point-cloud-networks-for-motion	0.9884	0.5601	0.1333	1.9286	1.5752	0.8153	3.4872	1.2442
dcms-motion-forecasting-with-dual-consistency	0.9902	0.5322	0.1094	1.7564	1.4768	0.7659	3.2515	1.135
Modell 151	0.8704	0.85	0.85	6.457	2.9719	2.9719	6.457	6.457
Modell 152	0.9846	0.5831	0.1376	1.929	1.7012	0.827	3.7811	1.2395
Modell 153	0.9139	0.8388	0.4931	3.7583	2.9838	1.6327	6.8853	3.0638
Modell 154	0.9833	0.6453	0.1699	2.0926	1.8763	0.8935	4.1783	1.3981
Modell 155	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 156	0.9898	0.5514	0.1207	1.8006	1.5959	0.8057	3.4648	1.1693
Modell 157	0.9878	0.5378	0.1155	1.7654	1.5349	0.8053	3.3216	1.1385
Modell 158	0.9895	0.6286	0.129	1.8691	1.8521	0.7854	4.1163	1.1872
Modell 159	0.9887	0.5766	0.1383	1.883	1.6572	0.8332	3.6604	1.2694
Modell 160	0.9883	0.5395	0.1143	1.7568	1.5599	0.8014	3.3814	1.2139
Modell 161	0.9793	0.5928	0.1657	2.0651	1.712	0.8683	3.7985	1.3707
Modell 162	0.979	0.6742	0.1884	2.0783	2.3148	0.9414	5.053	1.409
Modell 163	0.9799	0.6142	0.6142	4.5214	1.7303	1.7303	3.827	3.827
Modell 164	0.9859	0.5601	0.1416	1.966	1.6225	0.8351	3.5641	1.2715
Modell 165	0.985	0.5876	0.1622	2.0414	1.7438	0.8879	3.7642	1.3718
Modell 166	0.9812	0.6542	0.1937	2.1405	1.9953	0.9776	4.3111	1.5183
gohome-graph-oriented-heatmap-output	0.9811	0.5724	0.1048	1.9834	1.6887	0.9425	3.6468	1.4503
Modell 168	0.987	0.6465	0.1615	2.0891	1.9673	0.908	4.3037	1.4413
Modell 169	0.8366	0.9572	0.9572	12.8813	7.1746	7.1746	12.8813	12.8813
Modell 170	0.9833	0.6306	0.6306	4.0092	1.8179	1.8179	4.0092	4.0092
Modell 171	0.8722	0.8348	0.8168	8.2618	3.5333	3.3861	7.8875	7.5673
Modell 172	0.9876	0.6085	0.1539	1.9737	1.7874	0.8367	4.0418	1.3222
Modell 173	0.9105	0.9563	0.4048	3.0322	4.7665	1.2684	10.8683	2.3377
Modell 174	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 175	0.983	0.8634	0.1864	2.1343	3.0009	0.8892	7.0697	1.4399
Modell 176	0.9815	0.6321	0.1891	2.2003	1.8768	0.9347	4.1366	1.5058
Modell 177	0.98	0.5905	0.1634	2.0585	1.706	0.8679	3.7786	1.364
Modell 178	0.8592	0.8677	0.8677	6.8531	2.7385	2.7385	6.1586	6.1586
Modell 179	0.9818	0.6237	0.1699	2.1368	1.7988	0.9096	3.9852	1.4424
Modell 180	0.9868	0.6305	0.2317	2.1485	1.8426	0.9193	4.1231	1.5334
Modell 181	0.9897	0.5275	0.1065	1.7313	1.5181	0.7709	3.2849	1.1057
Modell 182	0.9758	0.7508	0.2887	2.6675	2.771	1.2052	5.7482	1.973
Modell 183	0.864	0.9386	0.9386	9.5077	4.6564	4.6564	9.5077	9.5077
ssl-lanes-self-supervised-learning-for-motion	0.9844	0.5671	0.1326	1.9433	1.6342	0.8401	3.5643	1.2493
Modell 185	0.9881	0.54	0.1223	1.8092	1.5111	0.7537	3.3645	1.137
Modell 186	0.8688	0.8715	0.5718	4.276	3.4549	1.8114	7.8828	3.5816
Modell 187	0.9298	0.7648	0.7648	5.8479	2.2831	2.2831	5.1534	5.1534
Modell 188	0.9893	0.5261	0.1101	1.6942	1.491	0.7623	3.2628	1.1337
Modell 189	0.8857	0.8348	0.8348	7.8875	3.5333	3.5333	7.8875	7.8875
Modell 190	0.1816	0.6574	0.1035	2.2793	14.9928	14.9112	4.1642	1.5849
Modell 191	0.9874	0.5503	0.1362	1.9461	1.5852	0.8181	3.47	1.2517
Modell 192	0.9833	0.575	0.154	2.0305	1.6547	0.8525	3.6489	1.3361
Modell 193	0.9762	0.8405	0.2186	2.3584	2.797	0.9877	6.6511	1.6639
Modell 194	0.9873	0.5791	0.1437	1.9309	1.7061	0.8142	3.7626	1.2651
Modell 195	0.9831	0.6008	0.1146	2.0712	1.7491	0.9518	3.8435	1.498
Modell 196	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7642	1.355
Modell 197	0.9197	0.7789	0.3983	3.0871	2.5448	1.4307	5.6608	2.3926
Modell 198	0.9563	0.6589	0.2096	2.225	2.2842	1.2904	4.3966	1.5956
Modell 199	0.9888	0.5606	0.1374	1.8392	1.6186	0.8157	3.5573	1.2425
Modell 200	0.9384	0.7347	0.7205	5.4699	2.1416	2.1	4.8748	4.7755
Modell 201	0.9846	0.5831	0.151	2.0214	1.6768	0.8605	3.6951	1.327
Modell 202	0.7834	0.9056	0.6785	5.1399	4.4349	2.2765	9.5225	4.4455
Modell 203	0.9268	0.7574	0.7574	5.054	2.1962	2.1962	5.054	5.054
Modell 204	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 205	0.9892	0.5563	0.1324	1.8872	1.6405	0.7917	3.6226	1.2124
Modell 206	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 207	0.9884	0.563	0.1354	1.8981	1.6602	0.7973	3.662	1.2283
Modell 208	0.973	0.7074	0.2471	2.4713	2.4627	1.1662	5.1875	1.7768
Modell 209	0.9808	0.637	0.1397	2.1093	2.1461	1.3818	4.227	1.4396
Modell 210	0.8676	0.8715	0.5369	3.9814	3.4549	1.7129	7.8828	3.287
Modell 211	0.9578	0.7294	0.5128	3.9753	2.232	1.6091	4.7064	3.2809
Modell 212	0.9818	0.6118	0.1048	2.1863	1.7812	0.9574	3.9003	1.4919
Modell 213	0.8879	0.912	0.912	8.8578	3.5646	3.5646	8.1634	8.1634
Modell 214	0.9857	0.583	0.1203	2.0584	1.6973	0.8688	3.7573	1.3639
Modell 215	0.8893	0.8902	0.6457	5.4818	4.4824	2.1201	9.4305	4.7874
Modell 216	0.98	0.5909	0.2333	2.3223	1.6737	0.9296	3.7541	1.6362
Modell 217	0.9815	0.6172	0.1592	2.1039	1.803	0.8779	4.0235	1.4095
Modell 218	0.9042	0.8117	0.8117	6.1454	2.3805	2.3805	5.451	5.451
Modell 219	0.9815	0.6288	0.1669	2.1164	1.8233	0.8995	4.0307	1.422
Modell 220	0.9836	0.6422	0.1823	2.3104	2.0029	1.1322	4.345	1.6453
Modell 221	0.9187	0.779	0.7392	5.6948	2.4611	2.3434	5.3231	5.0003
Modell 222	0.982	0.591	0.1652	2.0725	1.7189	0.8803	3.7918	1.3781
query-centric-trajectory-prediction	0.9887	0.5257	0.1056	1.6934	1.5234	0.7340	3.3420	1.0666
Modell 224	0.9877	0.5764	0.1418	1.9773	1.6724	0.8393	3.6518	1.2828
Modell 225	0.9671	0.8097	0.4177	3.4799	2.8104	1.3998	6.5063	2.7821
Modell 226	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 227	0.9567	0.7802	0.4051	3.5141	2.6885	1.4608	6.2682	2.8196
Modell 228	0.9637	0.8705	0.5423	4.255	3.7408	1.7691	8.3529	3.5606
Modell 229	0.9912	0.5528	0.1075	1.794	1.6124	0.7819	3.5116	1.1127
Modell 230	0.9922	0.6133	0.142	2.1114	1.8386	0.9116	4.0309	1.4503
Modell 231	0.9883	0.5586	0.136	1.8915	1.6588	0.7943	3.6568	1.2212
Modell 232	0.9807	0.5871	0.1611	2.0482	1.6906	0.8626	3.7418	1.3537
Modell 233	0.9518	0.6808	0.6808	5.0872	1.9424	1.9424	4.3927	4.3927
Modell 234	0.9506	0.6982	0.6982	4.6211	2.0489	2.0489	4.6211	4.6211
Modell 235	0.7064	0.9476	0.9476	11.4556	5.7132	5.7132	11.4556	11.4556
Modell 236	0.9814	0.5891	0.1674	2.0789	1.7055	0.8741	3.7705	1.3844
Modell 237	0.9656	0.7032	0.2611	2.8381	2.3379	1.2774	5.0578	2.1774
Modell 238	0.9834	0.5967	0.1623	2.0699	1.6968	0.8667	3.7496	1.3755
Modell 239	0.9862	0.5998	0.1352	1.8678	1.6702	0.8026	3.7724	1.2339
hivt-hierarchical-vector-transformer-for	0.9888	0.5473	0.1267	1.8422	1.5984	0.7735	3.5328	1.1693
Modell 241	0.9623	0.9878	0.3135	2.7502	7.4994	1.2128	17.191	2.0558
Modell 242	0.9834	0.5935	0.1606	2.0374	1.7001	0.856	3.775	1.3429
Modell 243	0.9588	0.6971	0.2508	2.6708	2.1728	1.1287	4.8418	1.9764
Modell 244	0.9894	0.5475	0.1177	1.7483	1.5737	0.8046	3.4467	1.1554
Modell 245	0.9896	0.5517	0.1209	1.8067	1.6072	0.8091	3.4945	1.1744
Modell 246	0.984	0.5795	0.1576	1.9618	1.6585	0.8579	3.6581	1.3432
Modell 247	0.8676	0.8715	0.5369	3.9814	3.4549	1.7129	7.8828	3.287
Modell 248	0.9756	0.639	0.1858	2.0592	1.8599	0.9191	4.0927	1.4475
hivt-hierarchical-vector-transformer-for	0.9891	0.5431	0.1221	1.8171	1.5619	0.7673	3.4449	1.146
Modell 250	0.9927	0.82	0.4181	3.3584	2.9076	1.3836	6.5416	2.6639
Modell 251	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7643	1.355
Modell 252	0.9868	0.6856	0.1308	2.1154	1.7414	0.9973	4.2372	1.4209
Modell 253	0.9511	0.7824	0.3591	2.9845	2.7262	1.3988	5.9819	2.29
Modell 254	0.9878	0.7159	0.7159	5.0682	2.2719	2.2719	5.0682	5.0682
Modell 255	0.98	0.6016	0.6016	4.3633	1.6557	1.6557	3.6689	3.6689
Modell 256	0.9886	0.5449	0.1168	1.7512	1.5689	0.789	3.4067	1.1602
Modell 257	0.9897	0.5467	0.1245	1.8347	1.5531	0.772	3.4533	1.1626
Modell 258	0.9875	0.5431	0.1124	1.7286	1.5327	0.7606	3.3611	1.1213
Modell 259	0.8892	0.8045	0.5201	3.4092	2.6784	1.4519	5.999	2.7148
Modell 260	0.8726	0.904	0.4083	3.191	3.3098	1.2687	8.0179	2.4966
Modell 261	0.9756	0.6097	0.1779	2.1286	1.7902	0.8832	4.0114	1.4341
Modell 262	0.9886	0.5696	0.1282	1.9211	1.6338	0.8468	3.5752	1.2494
Modell 263	0.9885	0.5573	0.1331	1.8932	1.6377	0.7933	3.614	1.2193
Modell 264	0.937	0.8574	0.5247	4.5742	4.7286	2.3101	9.7385	3.8798
Modell 265	0.9899	0.5921	0.1255	1.8868	1.8108	0.8026	4.0551	1.2321
Modell 266	0.9891	0.5955	0.5955	3.8239	1.7284	1.7284	3.8239	3.8239
Modell 267	0.9812	0.5877	0.162	2.0539	1.7019	0.8703	3.7624	1.3622
Modell 268	0.9762	0.6133	0.2208	2.2641	1.7721	0.9602	3.9013	1.5696
Modell 269	0.9725	0.6567	0.6567	4.1159	1.8525	1.8525	4.1159	4.1159
Modell 270	0.8332	0.8917	0.5458	4.1094	10634487.5868	155985.7998	8.6403	3.4149
Modell 271	0.8676	0.8715	0.5369	3.9814	3.4549	1.7129	7.8828	3.287
Modell 272	0.8988	0.8884	0.7382	5.6682	2.9871	2.4191	7.0155	4.9738
Modell 273	0.9805	0.5927	0.1689	2.0776	1.7288	0.8716	3.8359	1.3832
Modell 274	0.9838	0.6001	0.1618	1.9623	1.7396	0.8341	3.9297	1.3393
Modell 275	0.9836	0.5873	0.1597	2.0495	1.7024	0.8679	3.7642	1.355
Modell 276	0.8965	0.8139	0.8139	6.5202	2.6003	2.6003	5.8257	5.8257
Modell 277	0.946	0.7494	0.6582	4.787	2.9337	2.0282	6.4175	4.0938
Modell 278	0.9913	0.5573	0.1207	1.7992	1.632	0.8344	3.5505	1.1568
Modell 279	0.8977	0.8122	0.6916	6.1315	2.9631	2.3432	6.8116	5.437
Modell 280	0.9814	0.5945	0.1638	2.0668	1.7252	0.8706	3.8222	1.3723
Modell 281	0.985	0.5988	0.1032	2.0759	1.7029	0.9106	3.6961	1.3814
Modell 282	0.97	0.6868	0.6868	4.1982	1.8684	1.8684	4.1982	4.1982
Modell 283	0.8982	0.8141	0.8141	5.4732	2.418	2.418	5.4732	5.4732
tnt-target-driven-trajectory-prediction	0.9889	0.7097	0.1656	2.1401	2.174	0.9097	4.9593	1.4457
Modell 285	0.916	0.7907	0.7119	5.0674	2.3053	2.0458	5.2734	4.6173
Modell 286	0.987	0.8556	0.1349	1.932	2.7484	0.7963	6.6845	1.2225
Modell 287	0.9829	0.6087	0.3264	2.882	1.7732	1.1741	3.8707	2.1875
Modell 288	0.8805	0.8696	0.8696	6.4158	2.9498	2.9498	6.4158	6.4158
Modell 289	0.9872	0.5715	0.1425	1.9902	1.6427	0.866	3.6103	1.3072
Modell 290	0.879	0.8388	0.5419	4.6814	3.0551	1.9767	6.7766	3.9867
Modell 291	0.9797	0.6001	0.1735	2.0179	1.7239	0.8536	3.8623	1.384
Modell 292	0.9033	0.8915	0.8915	8.0293	3.9358	3.9358	8.0293	8.0293
Modell 293	0.9836	0.5828	0.158	2.0408	1.6837	0.8615	3.7242	1.3464
Modell 294	0.9842	0.7081	0.1522	2.0115	2.0558	0.8406	4.8659	1.3171
Modell 295	0.9884	0.5625	0.1472	1.8566	1.6214	0.8335	3.5485	1.2955
Modell 296	0.9889	0.7097	0.1656	2.1401	2.174	0.9097	4.9593	1.4457
Modell 297	0.9842	0.6779	0.1823	2.3691	1.986	1.0267	4.4898	1.7883
Modell 298	0.9845	0.5984	0.5984	4.435	1.6997	1.6997	3.7406	3.7406
Modell 299	0.9176	0.7701	0.7701	5.9661	2.2923	2.2923	5.2717	5.2717