Click on a measure to sort the table accordingly. See below for a more detailed description.
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
BIG_HA 1. | 47.1 | -37.9 ±24.1 | 0.0 | 0.0% | 100.0% | 213,867 | 564,228 | 0 (nan) | 0 (nan) | 887.9 | Public |
Anonymous submission | |||||||||||
CDT 2. | 48.3 | -64.5 ±16.9 | 0.1 | 0.0% | 99.4% | 364,642 | 563,672 | 72 (730.7) | 64 (649.5) | 46.9 | Public |
Anonymous submission | |||||||||||
terry_T 3. | 67.1 | 2.5 ±6.9 | 12.1 | 0.4% | 83.9% | 96,372 | 448,005 | 5,756 (279.4) | 11,270 (547.1) | 34.7 | Public |
Anonymous submission | |||||||||||
XYHv2 4. | 64.3 | 39.9 ±12.4 | 23.8 | 9.9% | 41.8% | 29,713 | 296,704 | 12,900 (272.1) | 12,911 (272.3) | 66.9 | Public |
Anonymous submission | |||||||||||
BU_CV 5. | 52.1 | 42.8 ±14.4 | 32.3 | 15.8% | 36.1% | 40,573 | 271,838 | 10,118 (195.2) | 9,426 (181.9) | 17.8 | Public |
Anonymous submission | |||||||||||
ZM 6. | 60.3 | 43.5 ±13.9 | 32.6 | 14.5% | 39.9% | 25,083 | 284,405 | 9,197 (185.4) | 8,849 (178.4) | 14.4 | Public |
Anonymous submission | |||||||||||
TM_track 7. | 66.3 | 41.1 ±14.9 | 32.8 | 13.2% | 41.3% | 27,606 | 287,511 | 17,408 (355.0) | 15,197 (309.9) | 2.5 | Public |
Anonymous submission | |||||||||||
GM_PHD 8. | 56.1 | 42.1 ±13.0 | 33.9 | 11.9% | 42.7% | 18,214 | 297,646 | 10,698 (226.4) | 10,864 (229.9) | 9.9 | Public |
Anonymous submission | |||||||||||
GM_PHD 9. | 57.1 | 36.4 ±14.1 | 33.9 | 4.1% | 57.3% | 23,723 | 330,767 | 4,607 (111.3) | 11,317 (273.5) | 38.4 | Public |
V. Eiselein, D. Arp, M. Pätzold, T. Sikora. Real-time Multi-Human Tracking using a Probability Hypothesis Density Filter and multiple detectors. In 9th IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2012. | |||||||||||
dcor 10. | 49.8 | 45.0 ±14.2 | 34.0 | 15.4% | 38.2% | 30,231 | 275,265 | 4,801 (93.7) | 8,498 (165.9) | 44.4 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
ReDetPast 11. | 57.1 | 44.3 ±14.8 | 34.9 | 17.3% | 36.7% | 32,113 | 271,343 | 10,962 (211.2) | 11,733 (226.0) | 3.3 | Public |
Anonymous submission | |||||||||||
GMPHD_KCF 12. | 61.8 | 39.6 ±13.6 | 36.6 | 8.8% | 43.3% | 50,903 | 284,228 | 5,811 (117.1) | 7,414 (149.4) | 3.3 | Public |
T. Kutschbach, E. Bochinski, V. Eiselein, T. Sikora. Sequential Sensor Fusion Combining Probability Hypothesis Density and Kernelized Correlation Filters for Multi-Object Tracking in Video Data. In International Workshop on Traffic and Street Surveillance for Safety and Security at IEEE AVSS 2017, 2017. | |||||||||||
AEb_Exp_4 13. | 44.3 | 38.6 ±16.8 | 39.3 | 14.8% | 46.4% | 16,841 | 327,217 | 2,206 (52.5) | 6,959 (165.7) | 66.9 | Public |
Anonymous submission | |||||||||||
IOU17 14. | 47.4 | 45.5 ±13.6 | 39.4 | 15.7% | 40.5% | 19,993 | 281,643 | 5,988 (119.6) | 7,404 (147.8) | 1,522.9 | Public |
E. Bochinski, V. Eiselein, T. Sikora. High-Speed Tracking-by-Detection Without Using Image Information. In International Workshop on Traffic and Street Surveillance for Safety and Security at IEEE AVSS 2017, 2017. | |||||||||||
reID2track 15. | 55.8 | 44.6 ±14.3 | 39.9 | 15.8% | 39.7% | 22,451 | 284,213 | 6,134 (123.6) | 13,786 (277.8) | 9.0 | Public |
Anonymous submission | |||||||||||
YT_T 16. | 53.3 | 45.4 ±13.4 | 40.3 | 16.0% | 35.7% | 25,425 | 275,050 | 7,652 (149.3) | 8,249 (160.9) | 11.4 | Public |
Anonymous submission | |||||||||||
EDA_GNN 17. | 45.8 | 45.5 ±13.8 | 40.5 | 15.6% | 40.6% | 25,685 | 277,663 | 4,091 (80.5) | 5,579 (109.8) | 39.3 | Public |
Paper ID 2713 | |||||||||||
QiMOT 18. | 50.1 | 47.2 ±13.1 | 40.8 | 15.5% | 39.9% | 18,907 | 274,828 | 4,320 (84.2) | 5,917 (115.4) | 1.8 | Public |
Anonymous submission | |||||||||||
PeriodMOT 19. | 52.2 | 43.8 ±13.2 | 40.9 | 14.7% | 42.0% | 21,941 | 290,194 | 4,910 (101.1) | 6,649 (136.9) | 66.9 | Public |
Anonymous submission | |||||||||||
TAR_1 20. | 35.8 | 51.6 ±11.9 | 41.4 | 21.7% | 28.7% | 33,514 | 235,859 | 3,629 (62.4) | 5,949 (102.2) | 5.6 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
EAMTT 21. | 53.1 | 42.6 ±13.3 | 41.8 | 12.7% | 42.7% | 30,711 | 288,474 | 4,488 (91.8) | 5,720 (117.0) | 12.0 | Public |
R. Sanchez-Matilla, F. Poiesi, A. Cavallaro. Online Multi-target Tracking with Strong and Weak Detections. In Computer Vision -- ECCV 2016 Workshops, 2016. | |||||||||||
PHD_LMP 22. | 50.8 | 45.9 ±13.1 | 42.5 | 15.5% | 37.9% | 27,946 | 272,196 | 4,977 (96.2) | 6,985 (135.0) | 29.4 | Public |
Anonymous submission | |||||||||||
ORCtracker 23. | 38.3 | 50.7 ±13.7 | 43.1 | 17.0% | 35.2% | 20,440 | 249,791 | 8,069 (144.8) | 11,188 (200.8) | 3,760.7 | Public |
Anonymous submission | |||||||||||
PHD_GM 24. | 39.9 | 48.8 ±13.4 | 43.2 | 19.1% | 35.2% | 26,260 | 257,971 | 4,407 (81.2) | 6,448 (118.8) | 22.3 | Public |
Anonymous submission | |||||||||||
LM_NN 25. | 43.3 | 45.1 ±13.3 | 43.2 | 14.8% | 46.2% | 10,834 | 296,451 | 2,286 (48.2) | 2,463 (51.9) | 2.5 | Public |
NEUCOM-D-18-03230 | |||||||||||
IOUT_Re 26. | 30.7 | 52.7 ±13.0 | 43.3 | 20.1% | 32.6% | 16,529 | 243,226 | 6,946 (122.1) | 6,520 (114.6) | 7.0 | Public |
Anonymous submission | |||||||||||
SNM17 27. | 53.7 | 46.8 ±13.8 | 43.4 | 16.2% | 37.1% | 25,104 | 271,042 | 4,213 (81.1) | 9,891 (190.3) | 0.8 | Public |
Anonymous submission | |||||||||||
Q_ls 28. | 42.5 | 50.2 ±14.4 | 43.6 | 19.7% | 37.3% | 23,143 | 253,151 | 4,414 (80.1) | 6,112 (110.9) | 1.8 | Public |
Anonymous submission | |||||||||||
DSA_MOT17 29. | 40.3 | 45.0 ±12.6 | 43.6 | 15.8% | 39.2% | 21,442 | 286,482 | 2,491 (50.6) | 3,824 (77.7) | 9.9 | Public |
Anonymous submission | |||||||||||
IDOHMPT 30. | 48.8 | 46.0 ±13.1 | 44.1 | 16.8% | 36.6% | 30,873 | 268,221 | 5,768 (109.9) | 9,663 (184.2) | 8.1 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
CEMT 31. | 34.9 | 49.3 ±12.6 | 44.4 | 16.8% | 38.5% | 21,711 | 261,808 | 2,696 (50.3) | 3,409 (63.6) | 5.8 | Public |
Anonymous submission | |||||||||||
MTDF17 32. | 43.8 | 49.6 ±13.9 | 45.2 | 18.9% | 33.1% | 37,124 | 241,768 | 5,567 (97.4) | 9,260 (162.0) | 1.2 | Public |
Anonymous submission | |||||||||||
TEM 33. | 41.2 | 49.1 ±12.6 | 45.4 | 17.0% | 38.3% | 22,119 | 261,797 | 3,439 (64.2) | 3,881 (72.4) | 8.2 | Public |
Anonymous submission | |||||||||||
NV_MC 34. | 37.1 | 49.1 ±13.9 | 45.7 | 19.0% | 38.0% | 16,850 | 267,923 | 2,446 (46.6) | 3,196 (60.9) | 0.3 | Public |
Anonymous submission | |||||||||||
STDIC 35. | 49.0 | 44.1 ±13.6 | 45.9 | 13.2% | 39.6% | 46,126 | 266,449 | 2,992 (56.7) | 5,143 (97.4) | 17,757.0 | Public |
Anonymous submission | |||||||||||
AEb_Exp_6 36. ![]() | 31.3 | 48.1 ±13.5 | 45.9 | 18.1% | 39.5% | 17,371 | 273,117 | 2,352 (45.6) | 4,994 (96.8) | 66.9 | Public |
Anonymous submission | |||||||||||
AEb 37. | 30.9 | 48.1 ±13.4 | 46.0 | 17.7% | 39.5% | 16,839 | 273,819 | 2,350 (45.7) | 5,275 (102.5) | 66.9 | Public |
Anonymous submission | |||||||||||
L_SORT 38. | 46.8 | 45.0 ±14.0 | 46.0 | 12.2% | 41.1% | 19,967 | 287,229 | 3,294 (67.1) | 8,292 (168.9) | 102.6 | Public |
Anonymous submission | |||||||||||
HCC 39. | 37.0 | 44.8 ±11.2 | 46.8 | 18.3% | 38.9% | 17,586 | 292,294 | 1,555 (32.3) | 2,221 (46.1) | 0.9 | Public |
Anonymous submission | |||||||||||
AFN17 40. | 27.6 | 51.5 ±13.0 | 46.9 | 20.6% | 35.5% | 22,391 | 248,420 | 2,593 (46.3) | 4,308 (77.0) | 1.8 | Public |
Paper ID 4411 | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
MHT_DAM 41. | 32.7 | 50.7 ±13.7 | 47.2 | 20.8% | 36.9% | 22,875 | 252,889 | 2,314 (41.9) | 2,865 (51.9) | 0.9 | Public |
C. Kim, F. Li, A. Ciptadi, J. Rehg. Multiple Hypothesis Tracking Revisited. In ICCV, 2015. | |||||||||||
REQT 42. | 51.7 | 43.9 ±14.2 | 47.4 | 13.1% | 45.8% | 34,309 | 279,030 | 2,986 (59.1) | 5,402 (106.9) | 64.1 | Public |
Anonymous submission | |||||||||||
FWT 43. | 31.2 | 51.3 ±13.1 | 47.6 | 21.4% | 35.2% | 24,101 | 247,921 | 2,648 (47.2) | 4,279 (76.3) | 0.2 | Public |
R. Henschel, L. Leal-Taixé, D. Cremers, B. Rosenhahn. Fusion of Head and Full-Body Detectors for Multi-Object Tracking. In Trajnet CVPRW, 2018. | |||||||||||
Qclc 44. | 29.9 | 54.0 ±14.3 | 47.7 | 23.3% | 30.7% | 22,374 | 232,212 | 4,748 (80.7) | 6,022 (102.3) | 1.8 | Public |
Anonymous submission | |||||||||||
TPbase17 45. | 53.0 | 43.3 ±15.0 | 48.2 | 16.2% | 36.6% | 49,992 | 265,815 | 4,194 (79.3) | 12,103 (228.8) | 22.2 | Public |
Anonymous submission | |||||||||||
FPSN 46. | 48.9 | 44.9 ±13.9 | 48.4 | 16.5% | 35.8% | 33,757 | 269,952 | 7,136 (136.8) | 14,491 (277.8) | 10.1 | Public |
S. Lee, E. Kim. Multiple Object Tracking via Feature Pyramid Siamese Networks. In IEEE ACCESS, 2018. | |||||||||||
HDTR 47. | 18.7 | 54.1 ±11.4 | 48.4 | 23.3% | 34.8% | 18,002 | 238,818 | 1,895 (32.9) | 2,693 (46.7) | 1.8 | Public |
COMOT 48. | 38.8 | 46.4 ±13.5 | 48.5 | 14.8% | 42.2% | 20,752 | 279,816 | 2,069 (41.0) | 4,606 (91.4) | 5.0 | Public |
Anonymous submission | |||||||||||
PV 49. | 43.0 | 48.5 ±14.5 | 48.6 | 18.2% | 34.9% | 27,889 | 258,689 | 4,173 (77.1) | 8,661 (159.9) | 3.5 | Public |
Anonymous submission | |||||||||||
RTRC 50. | 41.4 | 48.5 ±14.2 | 48.6 | 18.7% | 35.7% | 34,180 | 252,859 | 3,490 (63.2) | 6,304 (114.2) | 9.8 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
TCF 51. | 42.4 | 48.3 ±13.6 | 48.7 | 18.9% | 35.1% | 36,274 | 252,092 | 3,530 (63.8) | 6,390 (115.5) | 6.4 | Public |
Anonymous submission | |||||||||||
SSOMOT 52. | 43.5 | 46.8 ±13.1 | 49.2 | 15.3% | 39.1% | 24,041 | 274,257 | 2,121 (41.3) | 4,897 (95.3) | 4.9 | Public |
Anonymous submission | |||||||||||
RTac 53. | 41.4 | 46.3 ±14.6 | 49.2 | 18.9% | 33.5% | 43,447 | 255,158 | 4,196 (76.6) | 6,056 (110.6) | 14.1 | Public |
Anonymous submission | |||||||||||
DH_TRK 54. | 26.3 | 54.1 ±13.0 | 49.2 | 21.6% | 28.4% | 36,196 | 216,670 | 5,918 (96.1) | 7,760 (126.0) | 1,775.7 | Public |
Anonymous submission | |||||||||||
TBNMF17 55. | 32.5 | 50.6 ±12.6 | 49.3 | 18.9% | 39.2% | 17,522 | 258,990 | 2,014 (37.2) | 4,432 (81.9) | 6.9 | Public |
Anonymous submission | |||||||||||
PHD_GSDL17 56. | 42.4 | 48.0 ±13.6 | 49.6 | 17.1% | 35.6% | 23,199 | 265,954 | 3,998 (75.6) | 8,886 (168.1) | 6.7 | Public |
Z. Fu, P. Feng, F. Angelini, J. Chambers, S. Naqvi. Particle PHD Filter based Multiple Human Tracking using Online Group-Structured Dictionary Learning. In IEEE Access, 2018. | |||||||||||
IDGA 57. | 28.6 | 49.9 ±12.2 | 50.3 | 22.1% | 36.7% | 37,060 | 243,148 | 2,426 (42.6) | 3,846 (67.6) | 59.2 | Public |
Anonymous submission | |||||||||||
MOT_BJ 58. | 39.5 | 50.4 ±12.3 | 51.0 | 18.2% | 34.1% | 30,911 | 245,831 | 3,296 (58.4) | 6,279 (111.3) | 0.0 | Public |
Anonymous submission | |||||||||||
SemiOMOT 59. | 26.8 | 52.4 ±15.0 | 51.0 | 22.6% | 34.6% | 23,660 | 242,953 | 2,070 (36.4) | 3,170 (55.7) | 0.7 | Public |
Anonymous submission | |||||||||||
HAM_SADF17 60. | 33.5 | 48.3 ±13.2 | 51.1 | 17.1% | 41.7% | 20,967 | 269,038 | 1,871 (35.8) | 3,020 (57.7) | 5.0 | Public |
Y. Yoon, A. Boragule, Y. Song, K. Yoon, M. Jeon. Online Multi-Object Tracking with Historical Appearance Matching and Scene Adaptive Detection Filtering. In IEEE AVSS, 2018. | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
NOTBD 61. | 30.4 | 53.9 ±12.7 | 51.2 | 21.5% | 35.6% | 28,912 | 228,356 | 2,964 (49.8) | 3,600 (60.5) | 0.3 | Public |
Anonymous submission | |||||||||||
EDMT17 62. | 31.3 | 50.0 ±13.9 | 51.3 | 21.6% | 36.3% | 32,279 | 247,297 | 2,264 (40.3) | 3,260 (58.0) | 0.6 | Public |
J. Chen, H. Sheng, Y. Zhang, Z. Xiong. Enhancing Detection Model for Multiple Hypothesis Tracking. In BMTT-PETS CVPRw, 2017. | |||||||||||
DGCT 63. | 19.8 | 54.5 ±13.1 | 51.3 | 21.0% | 35.4% | 10,471 | 243,143 | 2,865 (50.3) | 4,889 (85.9) | 7.0 | Public |
CJY, HYW, KHW @ HRI-SH | |||||||||||
ts_WCFMT 64. | 41.8 | 48.4 ±13.6 | 51.4 | 21.0% | 32.5% | 32,037 | 255,472 | 3,410 (62.3) | 6,351 (116.1) | 1.0 | Public |
Anonymous submission | |||||||||||
yt_face 65. | 26.6 | 52.6 ±13.1 | 51.5 | 23.0% | 35.9% | 23,894 | 241,489 | 2,047 (35.8) | 2,827 (49.4) | 2.2 | Public |
Anonymous submission | |||||||||||
MHT_bLSTM 66. | 37.6 | 47.5 ±12.6 | 51.9 | 18.2% | 41.7% | 25,981 | 268,042 | 2,069 (39.4) | 3,124 (59.5) | 1.9 | Public |
C. Kim, F. Li, J. Rehg. Multi-object Tracking with Neural Gating Using Bilinear LSTM. In ECCV, 2018. | |||||||||||
TBD17_1 67. | 30.5 | 51.4 ±11.7 | 52.0 | 18.5% | 33.2% | 24,261 | 247,195 | 2,985 (53.1) | 6,611 (117.7) | 1,183.8 | Public |
Anonymous submission | |||||||||||
AM_ADM17 68. | 36.1 | 48.1 ±13.8 | 52.1 | 13.4% | 39.7% | 25,061 | 265,495 | 2,214 (41.8) | 5,027 (94.9) | 5.7 | Public |
S. Lee, M. Kim, S. Bae, Learning Discriminative Appearance Models for Online Multi-Object Tracking with Appearance Discriminability Measures, In IEEE Access, 2018. | |||||||||||
WCFMT17 69. | 41.3 | 47.3 ±16.0 | 52.3 | 21.9% | 30.7% | 43,253 | 250,302 | 3,556 (63.9) | 6,071 (109.1) | 1.0 | Public |
Anonymous submission | |||||||||||
TPM 70. | 24.2 | 54.2 ±13.0 | 52.6 | 22.8% | 37.5% | 13,739 | 242,730 | 1,824 (32.0) | 2,472 (43.4) | 0.8 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
BnW 71. | 26.3 | 52.5 ±15.3 | 52.6 | 18.7% | 36.7% | 19,192 | 245,765 | 2,822 (50.0) | 5,610 (99.4) | 2.5 | Public |
Anonymous submission | |||||||||||
MOTDT17 72. | 29.9 | 50.9 ±11.9 | 52.7 | 17.5% | 35.7% | 24,069 | 250,768 | 2,474 (44.5) | 5,317 (95.7) | 18.3 | Public |
C. Long, A. Haizhou, Z. Zijie, S. Chong. Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-identification. In ICME, 2018. | |||||||||||
Sn_PBC 73. | 30.8 | 51.3 ±11.7 | 53.4 | 17.4% | 35.2% | 21,255 | 251,256 | 2,394 (43.2) | 6,148 (110.8) | 14.8 | Public |
Anonymous submission | |||||||||||
TOPA 74. | 27.3 | 51.8 ±13.5 | 53.4 | 19.6% | 33.1% | 27,603 | 241,546 | 2,668 (46.7) | 5,790 (101.2) | 443.9 | Public |
Anonymous submission | |||||||||||
DTBasline 75. | 27.2 | 51.1 ±11.7 | 53.4 | 16.7% | 35.5% | 20,309 | 253,245 | 2,549 (46.2) | 5,910 (107.2) | 22.2 | Public |
Anonymous submission | |||||||||||
PA_MOT17 76. | 26.0 | 51.6 ±13.5 | 53.5 | 18.9% | 33.5% | 28,794 | 241,704 | 2,635 (46.1) | 5,808 (101.6) | 710.3 | Public |
Anonymous submission | |||||||||||
SRPN17 77. | 33.8 | 51.0 ±11.7 | 53.5 | 16.8% | 35.1% | 21,011 | 252,808 | 2,596 (47.0) | 5,981 (108.4) | 4.1 | Public |
Anonymous submission | |||||||||||
DEEP_TAMA 78. | 29.7 | 50.3 ±13.3 | 53.5 | 19.2% | 37.5% | 25,479 | 252,996 | 2,192 (39.7) | 3,978 (72.1) | 1.5 | Public |
for journal submission | |||||||||||
hpmmt17 79. | 24.2 | 51.2 ±11.8 | 53.6 | 17.3% | 34.9% | 21,957 | 250,891 | 2,292 (41.3) | 6,108 (110.0) | 44,392.5 | Public |
Anonymous submission | |||||||||||
CRF_TRA 80. | 21.0 | 53.1 ±12.1 | 53.7 | 24.2% | 30.7% | 27,194 | 234,991 | 2,518 (43.2) | 4,918 (84.3) | 1.8 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
MOT_test 81. | 27.7 | 51.6 ±11.9 | 53.9 | 17.3% | 35.5% | 21,419 | 249,059 | 2,384 (42.7) | 5,613 (100.5) | 7.8 | Public |
Anonymous submission | |||||||||||
HIK_MOT17 82. | 19.6 | 53.9 ±13.7 | 54.3 | 23.7% | 32.0% | 27,656 | 230,042 | 2,386 (40.3) | 4,192 (70.8) | 5.4 | Public |
jCC 83. | 26.3 | 51.2 ±14.5 | 54.5 | 20.9% | 37.0% | 25,937 | 247,822 | 1,802 (32.1) | 2,984 (53.2) | 1.8 | Public |
M. Keuper, S. Tang, B. Andres, T. Brox, B. Schiele. Motion Segmentation amp; Multiple Object Tracking by Correlation Co-Clustering. In IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018. | |||||||||||
eHAF17 84. | 24.8 | 51.8 ±13.2 | 54.7 | 23.4% | 37.9% | 33,212 | 236,772 | 1,834 (31.6) | 2,739 (47.2) | 0.7 | Public |
H. Sheng, Y. Zhang, J. Chen, Z. Xiong, J. Zhang. Heterogeneous Association Graph Fusion for Target Association in Multiple Object Tracking. In IEEE Transactions on Circuits and Systems for Video Technology, 2018. | |||||||||||
CMT 85. | 18.8 | 52.0 ±13.2 | 54.8 | 23.3% | 37.7% | 31,660 | 237,547 | 1,827 (31.6) | 2,738 (47.3) | 10.2 | Public |
Anonymous submission | |||||||||||
DMAN 86. | 34.8 | 48.2 ±12.3 | 55.7 | 19.3% | 38.3% | 26,218 | 263,608 | 2,194 (41.2) | 5,378 (100.9) | 0.3 | Public |
J. Zhu, H. Yang, N. Liu, M. Kim, W. Zhang, M. Yang. Online Multi-Object Tracking with Dual Matching Attention Networks. In ECCV, 2018. | |||||||||||
TLMHT 87. | 32.8 | 50.6 ±12.5 | 56.5 | 17.6% | 43.4% | 22,213 | 255,030 | 1,407 (25.7) | 2,079 (37.9) | 2.6 | Public |
H. Sheng, J. Chen, Y. Zhang, W. Ke, Z. Xiong, J. Yu. Iterative Multiple Hypothesis Tracking with Tracklet-level Association. In IEEE Transactions on Circuits and Systems for Video Technology, 2018. | |||||||||||
SAS_MOT17 88. | 42.0 | 44.2 ±12.2 | 57.2 | 16.1% | 44.3% | 29,473 | 283,611 | 1,529 (30.7) | 2,644 (53.2) | 4.8 | Public |
Anonymous submission | |||||||||||
LSST17O 89. | 29.7 | 52.7 ±13.3 | 57.9 | 17.9% | 36.6% | 22,512 | 241,936 | 2,167 (37.9) | 7,443 (130.3) | 1.8 | Public |
Anonymous submission | |||||||||||
eTC17 90. | 24.3 | 51.9 ±12.8 | 58.0 | 23.5% | 35.5% | 37,311 | 231,658 | 2,294 (38.9) | 2,917 (49.5) | 0.7 | Public |
Anonymous submission | |||||||||||
Tracker | Avg Rank | MOTA | IDF1 | MT | ML | FP | FN | ID Sw. | Frag | Hz | Detector |
LSST17 91. | 24.8 | 54.7 ±12.9 | 62.3 | 20.4% | 40.1% | 26,091 | 228,434 | 1,243 (20.9) | 3,726 (62.6) | 1.5 | Public |
Anonymous submission | |||||||||||
ISDH_HDAv2 92. | 25.1 | 54.5 ±14.5 | 65.9 | 26.4% | 32.1% | 46,693 | 207,093 | 3,010 (47.6) | 6,000 (94.8) | 3.6 | Public |
MM-008988/ IEEE Transactions on Multimedia |
Sequences | Frames | Trajectories | Boxes |
21 | 17757 | 2355 | 564228 |
Sequence difficulty (from easiest to hardest, measured by average MOTA)
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Measure | Better | Perfect | Description |
Avg Rank | lower | 1 | This is the rank of each tracker averaged over all present evaluation measures. |
MOTA | higher | 100 % | Multiple Object Tracking Accuracy [1]. This measure combines three error sources: false positives, missed targets and identity switches. |
MOTP | higher | 100 % | Multiple Object Tracking Precision [1]. The misalignment between the annotated and the predicted bounding boxes. |
IDF1 | higher | 100 % | ID F1 Score [2]. The ratio of correctly identified detections over the average number of ground-truth and computed detections. |
FAF | lower | 0 | The average number of false alarms per frame. |
MT | higher | 100 % | Mostly tracked targets. The ratio of ground-truth trajectories that are covered by a track hypothesis for at least 80% of their respective life span. |
ML | lower | 0 % | Mostly lost targets. The ratio of ground-truth trajectories that are covered by a track hypothesis for at most 20% of their respective life span. |
FP | lower | 0 | The total number of false positives. |
FN | lower | 0 | The total number of false negatives (missed targets). |
ID Sw. | lower | 0 | The total number of identity switches. Please note that we follow the stricter definition of identity switches as described in [3]. |
Frag | lower | 0 | The total number of times a trajectory is fragmented (i.e. interrupted during tracking). |
Hz | higher | Inf. | Processing speed (in frames per second excluding the detector) on the benchmark. |
Symbol | Description |
This is an online (causal) method, i.e. the solution is immediately available with each incoming frame and cannot be changed at any later time. | |
This method used the provided detection set as input. | |
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This entry has been submitted or updated less than a week ago. |
[1] | Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. Image and Video Processing, 2008(1):1-10, 2008. |
[2] | Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking. In ECCV workshop on Benchmarking Multi-Target Tracking, 2016. |
[3] | Learning to associate: HybridBoosted multi-target tracker for crowded scene. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2009. |