Benchmark:
MOT16 |
Short name:
AM_ADM
Detector:
Public
Description:
n/a
Reference:
S. Lee, M. Kim, S. Bae, Learning Discriminative Appearance Models for Online Multi-Object Tracking with Appearance Discriminability Measures, In IEEE Access, 2018.
Last submitted:
July 05, 2018 (6 years ago)
Published:
July 13, 2018 at 08:39:00 CET
Submissions:
1
Project page / code:
n/a
Open source:
No
Hardware:
3.4GHZ, 1Core
Runtime:
5.8 Hz
Benchmark performance:
| Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
| MOT16 | 40.1 | 43.8 | 33.4 | 54 (7.1) | 351 (46.2) | 8,503 | 99,891 | 45.2 | 90.6 | 33.8 | 33.3 | 35.6 | 74.6 | 35.5 | 71.1 | 78.8 | 1.4 | 789 (17.5) | 1,736 (38.4) |
Detailed performance:
| Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
| MOT16-01 | 26.3 | 33.1 | 27.4 | 2 | 12 | 424 | 4,258 | 33.4 | 83.4 | 32.0 | 23.7 | 34.7 | 64.0 | 25.4 | 63.4 | 76.1 | 0.9 | 28 | 66 |
| MOT16-03 | 50.3 | 50.3 | 38.0 | 28 | 31 | 3,517 | 48,181 | 53.9 | 94.1 | 36.5 | 39.7 | 37.8 | 78.3 | 42.1 | 73.5 | 79.5 | 2.3 | 311 | 791 |
| MOT16-06 | 36.8 | 46.9 | 34.0 | 12 | 114 | 848 | 6,334 | 45.1 | 86.0 | 36.5 | 31.9 | 43.0 | 60.5 | 34.6 | 66.0 | 76.7 | 0.7 | 113 | 204 |
| MOT16-07 | 23.9 | 28.7 | 21.0 | 0 | 23 | 1,368 | 10,940 | 33.0 | 79.7 | 18.4 | 24.6 | 20.0 | 62.6 | 26.2 | 63.5 | 74.4 | 2.7 | 119 | 294 |
| MOT16-08 | 24.6 | 24.9 | 21.5 | 3 | 29 | 720 | 11,816 | 29.4 | 87.2 | 20.2 | 22.9 | 21.8 | 71.2 | 24.2 | 71.7 | 80.5 | 1.2 | 88 | 132 |
| MOT16-12 | 37.9 | 47.3 | 35.8 | 8 | 39 | 568 | 4,540 | 45.3 | 86.9 | 38.6 | 33.3 | 40.7 | 74.4 | 36.0 | 69.1 | 79.1 | 0.6 | 47 | 71 |
| MOT16-14 | 19.0 | 31.4 | 22.5 | 1 | 103 | 1,058 | 13,822 | 25.2 | 81.5 | 27.1 | 18.8 | 29.3 | 63.6 | 19.9 | 64.5 | 76.6 | 1.4 | 83 | 178 |
Raw data: