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Challenge and Dataset on Large-scale Human-centric Video Analysis in Complex Events (HiEve) |
Benchmark
performance:
MOTA | w_MOTA | IDF1 | MT | ML | FP | FN | ID_Sw | ID_Sw_DT | Frag | MOTP |
---|---|---|---|---|---|---|---|---|---|---|
35.5508 | 31.1281 | 30.9966 | 11.3326 | 43.7566 | 2993 | 37893 | 4019 | 77 | 3048 | 75.9995 |
Detailed
performance:
MOTA | w_MOTA | IDF1 | MT | ML | FP | FN | ID_Sw | ID_Sw_DT | Frag | MOTP | |
---|---|---|---|---|---|---|---|---|---|---|---|
hm_in_waiting_hall (ID:20) | 67.0159 | 65.0028 | 47.7324 | 57.1429 | 8.1633 | 889 | 2655 | 391 | 6 | 312 | 79.6560 |
hm_in_bus (ID:21) | 7.4776 | 3.4776 | 12.0314 | 0.0000 | 76.6667 | 11 | 870 | 47 | 1 | 30 | 68.1390 |
hm_in_dining_room2 (ID:22) | 15.6073 | 10.6675 | 15.8107 | 3.8835 | 36.8932 | 453 | 6977 | 762 | 12 | 621 | 68.8154 |
hm_in_lab2 (ID:23) | 70.8965 | 65.5358 | 39.4757 | 64.2857 | 21.4286 | 31 | 1065 | 209 | 6 | 177 | 77.3881 |
hm_in_subway_station (ID:24) | 4.8768 | -3.4690 | 8.4791 | 0.3040 | 75.3799 | 365 | 11966 | 445 | 28 | 305 | 68.7707 |
hm_in_passage (ID:25) | 18.0995 | 12.8337 | 21.9533 | 0.0000 | 28.7356 | 179 | 4224 | 570 | 8 | 337 | 70.9646 |
hm_in_fighting4 (ID:26) | 32.0161 | 29.8661 | 29.2324 | 11.7647 | 41.1765 | 320 | 2054 | 155 | 2 | 152 | 75.7063 |
hm_in_shopping_mall3 (ID:27) | 59.7914 | 55.8544 | 35.0141 | 32.2581 | 6.4516 | 87 | 1384 | 572 | 5 | 421 | 79.2941 |
hm_in_restaurant (ID:28) | 40.8606 | 31.3857 | 33.0266 | 15.0000 | 40.0000 | 153 | 1198 | 147 | 6 | 129 | 70.3659 |
hm_in_accident (ID:29) | 44.2557 | 42.4515 | 42.5041 | 24.0000 | 28.0000 | 152 | 984 | 111 | 1 | 107 | 78.9420 |
hm_in_stair3 (ID:30) | 31.7196 | 31.7196 | 33.1453 | 2.2222 | 11.1111 | 20 | 1150 | 184 | 0 | 100 | 77.6560 |
hm_in_crossroad (ID:31) | 63.3394 | 63.3394 | 50.4057 | 57.7778 | 6.6667 | 71 | 535 | 202 | 0 | 135 | 75.6796 |
hm_in_robbery (ID:32) | 37.2968 | 35.7854 | 35.8757 | 20.0000 | 42.5000 | 262 | 2831 | 224 | 2 | 222 | 73.2289 |