Motion Forecasting On Argoverse Cvpr 2020
المقاييس
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)
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
| اسم النموذج | 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) |
|---|---|---|---|---|---|---|---|---|
| النموذج 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 |
| النموذج 3 | 0.9263 | 0.7498 | 0.7498 | 4.9209 | 2.1686 | 2.1686 | 4.9209 | 4.9209 |
| النموذج 4 | 0.8857 | 0.8348 | 0.8348 | 7.8875 | 3.5333 | 3.5333 | 7.8875 | 7.8875 |
| النموذج 5 | 0.9183 | 0.7352 | 0.5901 | 4.0999 | 2.3865 | 1.6055 | 5.488 | 3.4055 |
| النموذج 6 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 7 | 0.9877 | 0.5791 | 0.1432 | 1.9162 | 1.6856 | 0.8186 | 3.7588 | 1.2754 |
| النموذج 8 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7642 | 1.355 |
| النموذج 9 | 0.9838 | 0.5701 | 0.1438 | 1.8752 | 1.6242 | 0.8331 | 3.58 | 1.2748 |
| النموذج 10 | 0.9124 | 0.8774 | 0.5504 | 4.1457 | 3.467 | 1.7875 | 7.4546 | 3.4512 |
| النموذج 11 | 0.9856 | 0.7161 | 0.1589 | 2.1082 | 2.2709 | 0.9583 | 5.0216 | 1.4138 |
| النموذج 12 | 0.9738 | 0.6685 | 0.6685 | 4.0972 | 1.8312 | 1.8312 | 4.0972 | 4.0972 |
| النموذج 13 | 0.9874 | 0.5598 | 0.1306 | 1.78 | 1.6244 | 0.81 | 3.5572 | 1.1996 |
| النموذج 14 | 0.9887 | 0.6467 | 0.1676 | 2.3613 | 1.9108 | 0.99 | 4.2597 | 1.6668 |
| النموذج 15 | 0.9671 | 0.8355 | 0.4889 | 4.1988 | 3.6495 | 1.888 | 8.1197 | 3.5044 |
| النموذج 16 | 0.9826 | 0.669 | 0.1849 | 2.083 | 2.0363 | 0.9105 | 4.5807 | 1.4341 |
| النموذج 17 | 0.9843 | 0.5665 | 0.1474 | 1.954 | 1.6217 | 0.8294 | 3.5508 | 1.2595 |
| النموذج 18 | 0.9759 | 0.6795 | 0.6795 | 4.1704 | 1.8705 | 1.8705 | 4.1704 | 4.1704 |
| النموذج 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 |
| النموذج 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 |
| النموذج 23 | 0.8441 | 0.8868 | 0.8868 | 8.7522 | 3.9771 | 3.9771 | 8.7522 | 8.7522 |
| النموذج 24 | 0.9185 | 0.7668 | 0.7668 | 5.7168 | 2.1875 | 2.1875 | 5.0224 | 5.0224 |
| النموذج 25 | 0.9691 | 0.6825 | 0.6825 | 4.2673 | 1.9123 | 1.9123 | 4.2673 | 4.2673 |
| النموذج 26 | 0.7042 | 0.9967 | 0.9893 | 26.4057 | 30.7524 | 28.3813 | 31.1513 | 25.7113 |
| النموذج 27 | 0.9882 | 0.5401 | 0.1223 | 1.8095 | 1.5097 | 0.7543 | 3.3621 | 1.1376 |
| النموذج 28 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 29 | 0.9883 | 0.5555 | 0.1297 | 1.8738 | 1.6266 | 0.7863 | 3.5825 | 1.1974 |
| النموذج 30 | 0.9835 | 0.6019 | 0.1586 | 2.044 | 1.7453 | 0.8642 | 3.8981 | 1.3496 |
| النموذج 31 | 0.9922 | 0.5154 | 0.1032 | 1.6820 | 1.4412 | 0.7282 | 3.1777 | 1.0566 |
| النموذج 32 | 0.9799 | 0.6036 | 0.1764 | 2.0408 | 1.73 | 0.8621 | 3.8782 | 1.4071 |
| النموذج 33 | 0.9848 | 0.6354 | 0.1677 | 2.0884 | 1.89 | 0.8888 | 4.2265 | 1.401 |
| النموذج 34 | 0.9829 | 0.5871 | 0.1471 | 1.9006 | 1.6864 | 0.8406 | 3.7477 | 1.2785 |
| النموذج 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 |
| النموذج 37 | 0.9931 | 0.5348 | 0.5348 | 3.2923 | 1.5407 | 1.5407 | 3.2923 | 3.2923 |
| النموذج 38 | 0.9835 | 0.5756 | 0.5756 | 3.5154 | 1.5969 | 1.5969 | 3.5154 | 3.5154 |
| النموذج 39 | 0.9875 | 0.6749 | 0.2585 | 2.8266 | 2.0414 | 1.1518 | 4.6325 | 2.1322 |
| النموذج 40 | 0.9834 | 0.6241 | 0.6241 | 3.9973 | 1.809 | 1.809 | 3.9973 | 3.9973 |
| النموذج 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 |
| النموذج 43 | 0.9898 | 0.5867 | 0.115 | 2.0978 | 1.9105 | 1.2187 | 3.8217 | 1.5582 |
| النموذج 44 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 45 | 0.9892 | 0.5754 | 0.1303 | 1.8584 | 1.6788 | 0.8194 | 3.7087 | 1.2186 |
| النموذج 46 | 0.9514 | 0.7892 | 0.4141 | 3.5654 | 2.9029 | 1.4811 | 6.8301 | 2.871 |
| النموذج 47 | 0.1475 | 1.0 | 0.8261 | 6.3362 | 38.9455 | 3.541 | 57.7046 | 5.6417 |
| النموذج 48 | 0.9118 | 0.8087 | 0.8087 | 5.8239 | 2.5344 | 2.5344 | 5.8239 | 5.8239 |
| النموذج 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 |
| النموذج 51 | 0.9812 | 0.6321 | 0.1791 | 2.0798 | 1.8436 | 0.9013 | 4.0875 | 1.4384 |
| النموذج 52 | 0.8934 | 0.7861 | 0.3389 | 2.7277 | 2.5904 | 1.1394 | 5.7132 | 2.0333 |
| النموذج 53 | 0.9849 | 0.6272 | 0.1591 | 2.006 | 1.8103 | 0.8703 | 3.9733 | 1.3505 |
| النموذج 54 | 0.9893 | 0.5435 | 0.1163 | 1.7963 | 1.5099 | 0.7797 | 3.3297 | 1.1675 |
| النموذج 55 | 0.9824 | 0.5966 | 0.1666 | 2.0714 | 1.7168 | 0.8702 | 3.8171 | 1.377 |
| النموذج 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 |
| النموذج 58 | 0.9864 | 0.5634 | 0.1408 | 1.9737 | 1.6262 | 0.8308 | 3.5851 | 1.2793 |
| النموذج 59 | 0.9485 | 0.7601 | 0.678 | 4.9666 | 3.0107 | 2.0839 | 6.688 | 4.2735 |
| النموذج 60 | 0.964 | 0.8355 | 0.5821 | 4.7203 | 3.6495 | 2.0775 | 8.1197 | 4.0258 |
| النموذج 61 | 0.9812 | 0.5926 | 0.1647 | 1.9981 | 1.7163 | 0.8809 | 3.801 | 1.3845 |
| النموذج 62 | 0.9866 | 0.5565 | 0.1427 | 1.9744 | 1.5851 | 0.8444 | 3.4838 | 1.28 |
| النموذج 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 |
| النموذج 65 | 0.9847 | 0.5764 | 0.1395 | 1.8988 | 1.645 | 0.8277 | 3.6029 | 1.2532 |
| النموذج 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 |
| النموذج 68 | 0.9568 | 0.7171 | 0.5363 | 4.2643 | 2.4032 | 1.6939 | 5.4621 | 3.5698 |
| النموذج 69 | 0.9909 | 0.553 | 0.1209 | 1.8188 | 1.6287 | 0.818 | 3.5263 | 1.1888 |
| النموذج 70 | 0.9825 | 0.6333 | 0.1732 | 2.2004 | 1.8785 | 0.9172 | 4.2259 | 1.506 |
| النموذج 71 | 0.9842 | 0.6178 | 0.154 | 2.0328 | 1.7737 | 0.8436 | 4.0033 | 1.3383 |
| النموذج 72 | 0.4323 | 0.9936 | 0.9312 | 24.3515 | 17.0122 | 12.6584 | 34.3376 | 23.657 |
| النموذج 73 | 0.9192 | 0.7773 | 0.7773 | 5.1247 | 2.2181 | 2.2181 | 5.1247 | 5.1247 |
| النموذج 74 | 0.9179 | 0.6576 | 0.5428 | 3.7921 | 1.9103 | 1.5031 | 4.2923 | 3.0976 |
| النموذج 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 |
| النموذج 77 | 0.4222 | 0.6517 | 0.3579 | 2.994 | 2.3896 | 1.8694 | 4.1008 | 2.2995 |
| النموذج 78 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 79 | 0.3525 | 0.737 | 0.6583 | 5.0426 | 22.3728 | 2.1476 | 25.4924 | 4.7166 |
| النموذج 80 | 0.9742 | 0.9083 | 0.5156 | 4.8253 | 5.5699 | 2.2968 | 11.0515 | 4.1309 |
| النموذج 81 | 0.9865 | 0.7452 | 0.1589 | 2.048 | 2.1902 | 0.848 | 4.915 | 1.3536 |
| النموذج 82 | 0.9776 | 0.7285 | 0.1951 | 2.1576 | 2.2283 | 0.9163 | 5.0944 | 1.4631 |
| النموذج 83 | 0.9815 | 0.6375 | 0.1865 | 2.0434 | 1.8637 | 0.8832 | 4.1511 | 1.4262 |
| النموذج 84 | 0.9876 | 0.718 | 0.3276 | 3.2327 | 2.4228 | 1.549 | 5.2943 | 2.5765 |
| النموذج 85 | 0.99 | 0.575 | 0.1266 | 1.8567 | 1.715 | 0.8285 | 3.7582 | 1.2403 |
| النموذج 86 | 0.9825 | 0.5981 | 0.1603 | 1.9863 | 1.7978 | 0.861 | 4.0415 | 1.3527 |
| النموذج 87 | 0.9891 | 0.5972 | 0.146 | 1.946 | 1.7338 | 0.8636 | 3.8476 | 1.3399 |
| النموذج 88 | 0.9816 | 0.5933 | 0.1217 | 2.1386 | 1.7995 | 0.9892 | 3.8357 | 1.5159 |
| النموذج 89 | 0.9875 | 0.5843 | 0.1258 | 1.9759 | 1.6791 | 0.8817 | 3.6321 | 1.2815 |
| النموذج 90 | 0.947 | 0.6688 | 0.3857 | 3.2277 | 1.9276 | 1.3568 | 4.2738 | 2.4881 |
| النموذج 91 | 0.9889 | 0.5862 | 0.148 | 1.9635 | 1.698 | 0.836 | 3.7395 | 1.2863 |
| النموذج 92 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 93 | 0.9877 | 0.6322 | 0.1707 | 2.1092 | 1.9536 | 0.8841 | 4.2854 | 1.4204 |
| النموذج 94 | 0.9848 | 0.6312 | 0.1635 | 2.0574 | 1.8397 | 0.8758 | 4.1061 | 1.3715 |
| النموذج 95 | 0.984 | 0.6151 | 0.1059 | 2.1898 | 1.8014 | 0.9779 | 3.9418 | 1.4953 |
| النموذج 96 | 0.9776 | 0.5968 | 0.1738 | 2.0975 | 1.731 | 0.8775 | 3.8592 | 1.4031 |
| النموذج 97 | 0.9888 | 0.5742 | 0.1327 | 1.9423 | 1.6492 | 0.8674 | 3.5879 | 1.2703 |
| النموذج 98 | 0.9805 | 0.6158 | 0.1666 | 2.0857 | 1.7762 | 0.8986 | 3.9079 | 1.3913 |
| النموذج 99 | 0.9839 | 0.6201 | 0.6201 | 3.9861 | 1.8062 | 1.8062 | 3.9861 | 3.9861 |
| النموذج 100 | 0.9044 | 0.8197 | 0.8197 | 6.1954 | 2.7291 | 2.7291 | 6.1954 | 6.1954 |
| النموذج 101 | 0.9408 | 0.8659 | 0.5203 | 3.8899 | 3.3858 | 1.684 | 7.6186 | 3.1954 |
| النموذج 102 | 0.9816 | 0.6329 | 0.1804 | 2.1001 | 1.9016 | 0.916 | 4.2119 | 1.4591 |
| النموذج 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 |
| النموذج 105 | 0.89 | 0.8602 | 0.8602 | 6.0771 | 2.7271 | 2.7271 | 6.0771 | 6.0771 |
| النموذج 106 | 0.9814 | 0.6353 | 0.1795 | 2.1037 | 1.8988 | 0.8943 | 4.2353 | 1.4645 |
| النموذج 107 | 0.9898 | 0.5814 | 0.1341 | 1.918 | 1.6561 | 0.8012 | 3.6496 | 1.2235 |
| النموذج 108 | 0.8654 | 0.9068 | 0.9068 | 6.992 | 3.2553 | 3.2553 | 6.992 | 6.992 |
| النموذج 109 | 0.2939 | 0.9999 | 0.8237 | 6.2931 | 32.9034 | 3.2331 | 46.7268 | 5.5987 |
| النموذج 110 | 0.9495 | 0.7756 | 0.3983 | 2.9967 | 2.7949 | 1.3502 | 6.0524 | 2.3501 |
| النموذج 111 | 0.9903 | 0.5579 | 0.121 | 1.8817 | 1.6117 | 0.813 | 3.5087 | 1.1873 |
| النموذج 112 | 0.9725 | 0.6344 | 0.2179 | 2.243 | 1.9044 | 0.9436 | 4.1917 | 1.5486 |
| النموذج 113 | 0.9769 | 0.6702 | 0.2129 | 2.1611 | 2.0401 | 0.9687 | 4.5299 | 1.5716 |
| النموذج 114 | 0.8697 | 0.889 | 0.889 | 6.7247 | 3.1088 | 3.1088 | 6.7247 | 6.7247 |
| النموذج 115 | 0.9826 | 0.6074 | 0.1619 | 2.0682 | 1.7365 | 0.8715 | 3.8482 | 1.3737 |
| النموذج 116 | 0.9699 | 0.7837 | 0.2189 | 2.3277 | 2.6392 | 0.9693 | 6.029 | 1.6332 |
| النموذج 117 | 0.9807 | 0.5852 | 0.1696 | 2.0993 | 1.6737 | 0.8858 | 3.6837 | 1.4049 |
| النموذج 118 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 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 |
| النموذج 122 | 0.9143 | 0.806 | 0.806 | 5.8185 | 2.5329 | 2.5329 | 5.8185 | 5.8185 |
| النموذج 123 | 0.9743 | 0.6879 | 0.3191 | 2.7237 | 2.0987 | 1.1624 | 4.6642 | 2.1036 |
| النموذج 124 | 0.832 | 0.9064 | 0.709 | 5.6071 | 5.8841 | 2.823 | 11.3051 | 4.9126 |
| النموذج 125 | 0.981 | 0.5962 | 0.1725 | 2.1136 | 1.7191 | 0.8883 | 3.8039 | 1.4192 |
| النموذج 126 | 0.7756 | 0.9238 | 0.9238 | 8.1441 | 3.9521 | 3.9521 | 8.1441 | 8.1441 |
| النموذج 127 | 0.9827 | 0.5875 | 0.1591 | 2.04 | 1.6883 | 0.862 | 3.7274 | 1.3456 |
| النموذج 128 | 0.9602 | 0.6278 | 0.214 | 2.2688 | 1.8335 | 0.9303 | 4.1274 | 1.5984 |
| النموذج 129 | 0.8983 | 0.8379 | 0.7805 | 6.0565 | 2.6883 | 2.4943 | 5.8451 | 5.362 |
| النموذج 130 | 0.991 | 0.7828 | 0.2904 | 3.2196 | 2.9576 | 1.4537 | 6.3673 | 2.5476 |
| النموذج 131 | 0.9718 | 0.8457 | 0.4903 | 3.7943 | 3.3035 | 1.6056 | 7.4299 | 3.0999 |
| النموذج 132 | 0.8857 | 0.8348 | 0.8348 | 7.8875 | 3.5333 | 3.5333 | 7.8875 | 7.8875 |
| النموذج 133 | 0.9865 | 0.7656 | 0.3969 | 3.1788 | 2.5888 | 1.4161 | 5.7465 | 2.4845 |
| النموذج 134 | 0.9808 | 0.6127 | 0.1779 | 2.4781 | 1.8312 | 1.0416 | 4.01 | 1.7936 |
| النموذج 135 | 0.9397 | 0.7411 | 0.3553 | 2.8147 | 2.2558 | 1.1807 | 5.1581 | 2.2379 |
| النموذج 136 | 0.958 | 0.802 | 0.3434 | 3.0901 | 3.0338 | 1.4024 | 7.0702 | 2.3957 |
| النموذج 137 | 0.9092 | 0.5887 | 0.1501 | 2.0058 | 11.3861 | 11.2834 | 3.7832 | 1.3114 |
| النموذج 138 | 0.9818 | 0.5889 | 0.1673 | 2.0717 | 1.7041 | 0.8663 | 3.7827 | 1.3772 |
| النموذج 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 |
| النموذج 141 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 142 | 0.7734 | 0.8151 | 0.6899 | 5.3363 | 2.8257 | 2.1564 | 6.3946 | 4.6394 |
| النموذج 143 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 144 | 0.9886 | 0.5577 | 0.1351 | 1.9175 | 1.6453 | 0.7949 | 3.6269 | 1.2235 |
| النموذج 145 | 0.9584 | 0.7471 | 0.3393 | 3.2021 | 2.4611 | 1.2522 | 5.5965 | 2.5305 |
| النموذج 146 | 0.9494 | 0.7301 | 0.2845 | 2.8131 | 2.1057 | 1.1343 | 4.8259 | 2.1187 |
| النموذج 147 | 0.8857 | 0.8348 | 0.8348 | 7.8875 | 3.5333 | 3.5333 | 7.8875 | 7.8875 |
| النموذج 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 |
| النموذج 151 | 0.8704 | 0.85 | 0.85 | 6.457 | 2.9719 | 2.9719 | 6.457 | 6.457 |
| النموذج 152 | 0.9846 | 0.5831 | 0.1376 | 1.929 | 1.7012 | 0.827 | 3.7811 | 1.2395 |
| النموذج 153 | 0.9139 | 0.8388 | 0.4931 | 3.7583 | 2.9838 | 1.6327 | 6.8853 | 3.0638 |
| النموذج 154 | 0.9833 | 0.6453 | 0.1699 | 2.0926 | 1.8763 | 0.8935 | 4.1783 | 1.3981 |
| النموذج 155 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 156 | 0.9898 | 0.5514 | 0.1207 | 1.8006 | 1.5959 | 0.8057 | 3.4648 | 1.1693 |
| النموذج 157 | 0.9878 | 0.5378 | 0.1155 | 1.7654 | 1.5349 | 0.8053 | 3.3216 | 1.1385 |
| النموذج 158 | 0.9895 | 0.6286 | 0.129 | 1.8691 | 1.8521 | 0.7854 | 4.1163 | 1.1872 |
| النموذج 159 | 0.9887 | 0.5766 | 0.1383 | 1.883 | 1.6572 | 0.8332 | 3.6604 | 1.2694 |
| النموذج 160 | 0.9883 | 0.5395 | 0.1143 | 1.7568 | 1.5599 | 0.8014 | 3.3814 | 1.2139 |
| النموذج 161 | 0.9793 | 0.5928 | 0.1657 | 2.0651 | 1.712 | 0.8683 | 3.7985 | 1.3707 |
| النموذج 162 | 0.979 | 0.6742 | 0.1884 | 2.0783 | 2.3148 | 0.9414 | 5.053 | 1.409 |
| النموذج 163 | 0.9799 | 0.6142 | 0.6142 | 4.5214 | 1.7303 | 1.7303 | 3.827 | 3.827 |
| النموذج 164 | 0.9859 | 0.5601 | 0.1416 | 1.966 | 1.6225 | 0.8351 | 3.5641 | 1.2715 |
| النموذج 165 | 0.985 | 0.5876 | 0.1622 | 2.0414 | 1.7438 | 0.8879 | 3.7642 | 1.3718 |
| النموذج 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 |
| النموذج 168 | 0.987 | 0.6465 | 0.1615 | 2.0891 | 1.9673 | 0.908 | 4.3037 | 1.4413 |
| النموذج 169 | 0.8366 | 0.9572 | 0.9572 | 12.8813 | 7.1746 | 7.1746 | 12.8813 | 12.8813 |
| النموذج 170 | 0.9833 | 0.6306 | 0.6306 | 4.0092 | 1.8179 | 1.8179 | 4.0092 | 4.0092 |
| النموذج 171 | 0.8722 | 0.8348 | 0.8168 | 8.2618 | 3.5333 | 3.3861 | 7.8875 | 7.5673 |
| النموذج 172 | 0.9876 | 0.6085 | 0.1539 | 1.9737 | 1.7874 | 0.8367 | 4.0418 | 1.3222 |
| النموذج 173 | 0.9105 | 0.9563 | 0.4048 | 3.0322 | 4.7665 | 1.2684 | 10.8683 | 2.3377 |
| النموذج 174 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 175 | 0.983 | 0.8634 | 0.1864 | 2.1343 | 3.0009 | 0.8892 | 7.0697 | 1.4399 |
| النموذج 176 | 0.9815 | 0.6321 | 0.1891 | 2.2003 | 1.8768 | 0.9347 | 4.1366 | 1.5058 |
| النموذج 177 | 0.98 | 0.5905 | 0.1634 | 2.0585 | 1.706 | 0.8679 | 3.7786 | 1.364 |
| النموذج 178 | 0.8592 | 0.8677 | 0.8677 | 6.8531 | 2.7385 | 2.7385 | 6.1586 | 6.1586 |
| النموذج 179 | 0.9818 | 0.6237 | 0.1699 | 2.1368 | 1.7988 | 0.9096 | 3.9852 | 1.4424 |
| النموذج 180 | 0.9868 | 0.6305 | 0.2317 | 2.1485 | 1.8426 | 0.9193 | 4.1231 | 1.5334 |
| النموذج 181 | 0.9897 | 0.5275 | 0.1065 | 1.7313 | 1.5181 | 0.7709 | 3.2849 | 1.1057 |
| النموذج 182 | 0.9758 | 0.7508 | 0.2887 | 2.6675 | 2.771 | 1.2052 | 5.7482 | 1.973 |
| النموذج 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 |
| النموذج 185 | 0.9881 | 0.54 | 0.1223 | 1.8092 | 1.5111 | 0.7537 | 3.3645 | 1.137 |
| النموذج 186 | 0.8688 | 0.8715 | 0.5718 | 4.276 | 3.4549 | 1.8114 | 7.8828 | 3.5816 |
| النموذج 187 | 0.9298 | 0.7648 | 0.7648 | 5.8479 | 2.2831 | 2.2831 | 5.1534 | 5.1534 |
| النموذج 188 | 0.9893 | 0.5261 | 0.1101 | 1.6942 | 1.491 | 0.7623 | 3.2628 | 1.1337 |
| النموذج 189 | 0.8857 | 0.8348 | 0.8348 | 7.8875 | 3.5333 | 3.5333 | 7.8875 | 7.8875 |
| النموذج 190 | 0.1816 | 0.6574 | 0.1035 | 2.2793 | 14.9928 | 14.9112 | 4.1642 | 1.5849 |
| النموذج 191 | 0.9874 | 0.5503 | 0.1362 | 1.9461 | 1.5852 | 0.8181 | 3.47 | 1.2517 |
| النموذج 192 | 0.9833 | 0.575 | 0.154 | 2.0305 | 1.6547 | 0.8525 | 3.6489 | 1.3361 |
| النموذج 193 | 0.9762 | 0.8405 | 0.2186 | 2.3584 | 2.797 | 0.9877 | 6.6511 | 1.6639 |
| النموذج 194 | 0.9873 | 0.5791 | 0.1437 | 1.9309 | 1.7061 | 0.8142 | 3.7626 | 1.2651 |
| النموذج 195 | 0.9831 | 0.6008 | 0.1146 | 2.0712 | 1.7491 | 0.9518 | 3.8435 | 1.498 |
| النموذج 196 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7642 | 1.355 |
| النموذج 197 | 0.9197 | 0.7789 | 0.3983 | 3.0871 | 2.5448 | 1.4307 | 5.6608 | 2.3926 |
| النموذج 198 | 0.9563 | 0.6589 | 0.2096 | 2.225 | 2.2842 | 1.2904 | 4.3966 | 1.5956 |
| النموذج 199 | 0.9888 | 0.5606 | 0.1374 | 1.8392 | 1.6186 | 0.8157 | 3.5573 | 1.2425 |
| النموذج 200 | 0.9384 | 0.7347 | 0.7205 | 5.4699 | 2.1416 | 2.1 | 4.8748 | 4.7755 |
| النموذج 201 | 0.9846 | 0.5831 | 0.151 | 2.0214 | 1.6768 | 0.8605 | 3.6951 | 1.327 |
| النموذج 202 | 0.7834 | 0.9056 | 0.6785 | 5.1399 | 4.4349 | 2.2765 | 9.5225 | 4.4455 |
| النموذج 203 | 0.9268 | 0.7574 | 0.7574 | 5.054 | 2.1962 | 2.1962 | 5.054 | 5.054 |
| النموذج 204 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 205 | 0.9892 | 0.5563 | 0.1324 | 1.8872 | 1.6405 | 0.7917 | 3.6226 | 1.2124 |
| النموذج 206 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 207 | 0.9884 | 0.563 | 0.1354 | 1.8981 | 1.6602 | 0.7973 | 3.662 | 1.2283 |
| النموذج 208 | 0.973 | 0.7074 | 0.2471 | 2.4713 | 2.4627 | 1.1662 | 5.1875 | 1.7768 |
| النموذج 209 | 0.9808 | 0.637 | 0.1397 | 2.1093 | 2.1461 | 1.3818 | 4.227 | 1.4396 |
| النموذج 210 | 0.8676 | 0.8715 | 0.5369 | 3.9814 | 3.4549 | 1.7129 | 7.8828 | 3.287 |
| النموذج 211 | 0.9578 | 0.7294 | 0.5128 | 3.9753 | 2.232 | 1.6091 | 4.7064 | 3.2809 |
| النموذج 212 | 0.9818 | 0.6118 | 0.1048 | 2.1863 | 1.7812 | 0.9574 | 3.9003 | 1.4919 |
| النموذج 213 | 0.8879 | 0.912 | 0.912 | 8.8578 | 3.5646 | 3.5646 | 8.1634 | 8.1634 |
| النموذج 214 | 0.9857 | 0.583 | 0.1203 | 2.0584 | 1.6973 | 0.8688 | 3.7573 | 1.3639 |
| النموذج 215 | 0.8893 | 0.8902 | 0.6457 | 5.4818 | 4.4824 | 2.1201 | 9.4305 | 4.7874 |
| النموذج 216 | 0.98 | 0.5909 | 0.2333 | 2.3223 | 1.6737 | 0.9296 | 3.7541 | 1.6362 |
| النموذج 217 | 0.9815 | 0.6172 | 0.1592 | 2.1039 | 1.803 | 0.8779 | 4.0235 | 1.4095 |
| النموذج 218 | 0.9042 | 0.8117 | 0.8117 | 6.1454 | 2.3805 | 2.3805 | 5.451 | 5.451 |
| النموذج 219 | 0.9815 | 0.6288 | 0.1669 | 2.1164 | 1.8233 | 0.8995 | 4.0307 | 1.422 |
| النموذج 220 | 0.9836 | 0.6422 | 0.1823 | 2.3104 | 2.0029 | 1.1322 | 4.345 | 1.6453 |
| النموذج 221 | 0.9187 | 0.779 | 0.7392 | 5.6948 | 2.4611 | 2.3434 | 5.3231 | 5.0003 |
| النموذج 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 |
| النموذج 224 | 0.9877 | 0.5764 | 0.1418 | 1.9773 | 1.6724 | 0.8393 | 3.6518 | 1.2828 |
| النموذج 225 | 0.9671 | 0.8097 | 0.4177 | 3.4799 | 2.8104 | 1.3998 | 6.5063 | 2.7821 |
| النموذج 226 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 227 | 0.9567 | 0.7802 | 0.4051 | 3.5141 | 2.6885 | 1.4608 | 6.2682 | 2.8196 |
| النموذج 228 | 0.9637 | 0.8705 | 0.5423 | 4.255 | 3.7408 | 1.7691 | 8.3529 | 3.5606 |
| النموذج 229 | 0.9912 | 0.5528 | 0.1075 | 1.794 | 1.6124 | 0.7819 | 3.5116 | 1.1127 |
| النموذج 230 | 0.9922 | 0.6133 | 0.142 | 2.1114 | 1.8386 | 0.9116 | 4.0309 | 1.4503 |
| النموذج 231 | 0.9883 | 0.5586 | 0.136 | 1.8915 | 1.6588 | 0.7943 | 3.6568 | 1.2212 |
| النموذج 232 | 0.9807 | 0.5871 | 0.1611 | 2.0482 | 1.6906 | 0.8626 | 3.7418 | 1.3537 |
| النموذج 233 | 0.9518 | 0.6808 | 0.6808 | 5.0872 | 1.9424 | 1.9424 | 4.3927 | 4.3927 |
| النموذج 234 | 0.9506 | 0.6982 | 0.6982 | 4.6211 | 2.0489 | 2.0489 | 4.6211 | 4.6211 |
| النموذج 235 | 0.7064 | 0.9476 | 0.9476 | 11.4556 | 5.7132 | 5.7132 | 11.4556 | 11.4556 |
| النموذج 236 | 0.9814 | 0.5891 | 0.1674 | 2.0789 | 1.7055 | 0.8741 | 3.7705 | 1.3844 |
| النموذج 237 | 0.9656 | 0.7032 | 0.2611 | 2.8381 | 2.3379 | 1.2774 | 5.0578 | 2.1774 |
| النموذج 238 | 0.9834 | 0.5967 | 0.1623 | 2.0699 | 1.6968 | 0.8667 | 3.7496 | 1.3755 |
| النموذج 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 |
| النموذج 241 | 0.9623 | 0.9878 | 0.3135 | 2.7502 | 7.4994 | 1.2128 | 17.191 | 2.0558 |
| النموذج 242 | 0.9834 | 0.5935 | 0.1606 | 2.0374 | 1.7001 | 0.856 | 3.775 | 1.3429 |
| النموذج 243 | 0.9588 | 0.6971 | 0.2508 | 2.6708 | 2.1728 | 1.1287 | 4.8418 | 1.9764 |
| النموذج 244 | 0.9894 | 0.5475 | 0.1177 | 1.7483 | 1.5737 | 0.8046 | 3.4467 | 1.1554 |
| النموذج 245 | 0.9896 | 0.5517 | 0.1209 | 1.8067 | 1.6072 | 0.8091 | 3.4945 | 1.1744 |
| النموذج 246 | 0.984 | 0.5795 | 0.1576 | 1.9618 | 1.6585 | 0.8579 | 3.6581 | 1.3432 |
| النموذج 247 | 0.8676 | 0.8715 | 0.5369 | 3.9814 | 3.4549 | 1.7129 | 7.8828 | 3.287 |
| النموذج 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 |
| النموذج 250 | 0.9927 | 0.82 | 0.4181 | 3.3584 | 2.9076 | 1.3836 | 6.5416 | 2.6639 |
| النموذج 251 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7643 | 1.355 |
| النموذج 252 | 0.9868 | 0.6856 | 0.1308 | 2.1154 | 1.7414 | 0.9973 | 4.2372 | 1.4209 |
| النموذج 253 | 0.9511 | 0.7824 | 0.3591 | 2.9845 | 2.7262 | 1.3988 | 5.9819 | 2.29 |
| النموذج 254 | 0.9878 | 0.7159 | 0.7159 | 5.0682 | 2.2719 | 2.2719 | 5.0682 | 5.0682 |
| النموذج 255 | 0.98 | 0.6016 | 0.6016 | 4.3633 | 1.6557 | 1.6557 | 3.6689 | 3.6689 |
| النموذج 256 | 0.9886 | 0.5449 | 0.1168 | 1.7512 | 1.5689 | 0.789 | 3.4067 | 1.1602 |
| النموذج 257 | 0.9897 | 0.5467 | 0.1245 | 1.8347 | 1.5531 | 0.772 | 3.4533 | 1.1626 |
| النموذج 258 | 0.9875 | 0.5431 | 0.1124 | 1.7286 | 1.5327 | 0.7606 | 3.3611 | 1.1213 |
| النموذج 259 | 0.8892 | 0.8045 | 0.5201 | 3.4092 | 2.6784 | 1.4519 | 5.999 | 2.7148 |
| النموذج 260 | 0.8726 | 0.904 | 0.4083 | 3.191 | 3.3098 | 1.2687 | 8.0179 | 2.4966 |
| النموذج 261 | 0.9756 | 0.6097 | 0.1779 | 2.1286 | 1.7902 | 0.8832 | 4.0114 | 1.4341 |
| النموذج 262 | 0.9886 | 0.5696 | 0.1282 | 1.9211 | 1.6338 | 0.8468 | 3.5752 | 1.2494 |
| النموذج 263 | 0.9885 | 0.5573 | 0.1331 | 1.8932 | 1.6377 | 0.7933 | 3.614 | 1.2193 |
| النموذج 264 | 0.937 | 0.8574 | 0.5247 | 4.5742 | 4.7286 | 2.3101 | 9.7385 | 3.8798 |
| النموذج 265 | 0.9899 | 0.5921 | 0.1255 | 1.8868 | 1.8108 | 0.8026 | 4.0551 | 1.2321 |
| النموذج 266 | 0.9891 | 0.5955 | 0.5955 | 3.8239 | 1.7284 | 1.7284 | 3.8239 | 3.8239 |
| النموذج 267 | 0.9812 | 0.5877 | 0.162 | 2.0539 | 1.7019 | 0.8703 | 3.7624 | 1.3622 |
| النموذج 268 | 0.9762 | 0.6133 | 0.2208 | 2.2641 | 1.7721 | 0.9602 | 3.9013 | 1.5696 |
| النموذج 269 | 0.9725 | 0.6567 | 0.6567 | 4.1159 | 1.8525 | 1.8525 | 4.1159 | 4.1159 |
| النموذج 270 | 0.8332 | 0.8917 | 0.5458 | 4.1094 | 10634487.5868 | 155985.7998 | 8.6403 | 3.4149 |
| النموذج 271 | 0.8676 | 0.8715 | 0.5369 | 3.9814 | 3.4549 | 1.7129 | 7.8828 | 3.287 |
| النموذج 272 | 0.8988 | 0.8884 | 0.7382 | 5.6682 | 2.9871 | 2.4191 | 7.0155 | 4.9738 |
| النموذج 273 | 0.9805 | 0.5927 | 0.1689 | 2.0776 | 1.7288 | 0.8716 | 3.8359 | 1.3832 |
| النموذج 274 | 0.9838 | 0.6001 | 0.1618 | 1.9623 | 1.7396 | 0.8341 | 3.9297 | 1.3393 |
| النموذج 275 | 0.9836 | 0.5873 | 0.1597 | 2.0495 | 1.7024 | 0.8679 | 3.7642 | 1.355 |
| النموذج 276 | 0.8965 | 0.8139 | 0.8139 | 6.5202 | 2.6003 | 2.6003 | 5.8257 | 5.8257 |
| النموذج 277 | 0.946 | 0.7494 | 0.6582 | 4.787 | 2.9337 | 2.0282 | 6.4175 | 4.0938 |
| النموذج 278 | 0.9913 | 0.5573 | 0.1207 | 1.7992 | 1.632 | 0.8344 | 3.5505 | 1.1568 |
| النموذج 279 | 0.8977 | 0.8122 | 0.6916 | 6.1315 | 2.9631 | 2.3432 | 6.8116 | 5.437 |
| النموذج 280 | 0.9814 | 0.5945 | 0.1638 | 2.0668 | 1.7252 | 0.8706 | 3.8222 | 1.3723 |
| النموذج 281 | 0.985 | 0.5988 | 0.1032 | 2.0759 | 1.7029 | 0.9106 | 3.6961 | 1.3814 |
| النموذج 282 | 0.97 | 0.6868 | 0.6868 | 4.1982 | 1.8684 | 1.8684 | 4.1982 | 4.1982 |
| النموذج 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 |
| النموذج 285 | 0.916 | 0.7907 | 0.7119 | 5.0674 | 2.3053 | 2.0458 | 5.2734 | 4.6173 |
| النموذج 286 | 0.987 | 0.8556 | 0.1349 | 1.932 | 2.7484 | 0.7963 | 6.6845 | 1.2225 |
| النموذج 287 | 0.9829 | 0.6087 | 0.3264 | 2.882 | 1.7732 | 1.1741 | 3.8707 | 2.1875 |
| النموذج 288 | 0.8805 | 0.8696 | 0.8696 | 6.4158 | 2.9498 | 2.9498 | 6.4158 | 6.4158 |
| النموذج 289 | 0.9872 | 0.5715 | 0.1425 | 1.9902 | 1.6427 | 0.866 | 3.6103 | 1.3072 |
| النموذج 290 | 0.879 | 0.8388 | 0.5419 | 4.6814 | 3.0551 | 1.9767 | 6.7766 | 3.9867 |
| النموذج 291 | 0.9797 | 0.6001 | 0.1735 | 2.0179 | 1.7239 | 0.8536 | 3.8623 | 1.384 |
| النموذج 292 | 0.9033 | 0.8915 | 0.8915 | 8.0293 | 3.9358 | 3.9358 | 8.0293 | 8.0293 |
| النموذج 293 | 0.9836 | 0.5828 | 0.158 | 2.0408 | 1.6837 | 0.8615 | 3.7242 | 1.3464 |
| النموذج 294 | 0.9842 | 0.7081 | 0.1522 | 2.0115 | 2.0558 | 0.8406 | 4.8659 | 1.3171 |
| النموذج 295 | 0.9884 | 0.5625 | 0.1472 | 1.8566 | 1.6214 | 0.8335 | 3.5485 | 1.2955 |
| النموذج 296 | 0.9889 | 0.7097 | 0.1656 | 2.1401 | 2.174 | 0.9097 | 4.9593 | 1.4457 |
| النموذج 297 | 0.9842 | 0.6779 | 0.1823 | 2.3691 | 1.986 | 1.0267 | 4.4898 | 1.7883 |
| النموذج 298 | 0.9845 | 0.5984 | 0.5984 | 4.435 | 1.6997 | 1.6997 | 3.7406 | 3.7406 |
| النموذج 299 | 0.9176 | 0.7701 | 0.7701 | 5.9661 | 2.2923 | 2.2923 | 5.2717 | 5.2717 |