Benchmark:
MOT17 |
Short name:
GMPHD_DAL
Detector:
Public
Description:
n/a
Reference:
N. Baisa. Online Multi-object Visual Tracking using a GM-PHD Filter with Deep Appearance Learning. In 2019 22th International Conference on Information Fusion (FUSION), 2019.
Last submitted:
March 17, 2019 (5 years ago)
Published:
March 18, 2019 at 00:02:01 CET
Submissions:
3
Project page / code:
Open source:
No
Hardware:
3 GHZ, 1 Core
Runtime:
3.4 Hz
Benchmark performance:
| Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
| MOT17 | 44.4 | 36.2 | 31.4 | 350 (14.9) | 927 (39.4) | 19,170 | 283,380 | 49.8 | 93.6 | 26.6 | 37.5 | 29.1 | 69.7 | 39.7 | 74.6 | 80.4 | 1.1 | 11,137 (223.7) | 13,900 (279.3) |
Detailed performance:
| Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
| MOT17-01-DPM | 21.8 | 19.5 | 17.6 | 2 | 14 | 63 | 4,873 | 24.4 | 96.2 | 17.2 | 18.0 | 18.1 | 64.0 | 18.5 | 72.6 | 77.8 | 0.1 | 107 | 170 |
| MOT17-01-FRCNN | 25.6 | 32.5 | 30.4 | 6 | 8 | 1,470 | 3,267 | 49.3 | 68.4 | 28.6 | 32.6 | 31.1 | 66.3 | 40.2 | 55.7 | 78.9 | 3.3 | 63 | 79 |
| MOT17-01-SDP | 37.0 | 27.7 | 25.7 | 7 | 5 | 1,066 | 2,765 | 57.1 | 77.6 | 17.9 | 37.4 | 19.6 | 60.5 | 44.4 | 60.3 | 78.3 | 2.4 | 234 | 249 |
| MOT17-03-DPM | 40.9 | 27.4 | 23.9 | 12 | 44 | 1,000 | 58,458 | 44.2 | 97.9 | 17.2 | 33.5 | 18.0 | 73.1 | 34.6 | 76.8 | 80.1 | 0.7 | 2,395 | 3,122 |
| MOT17-03-FRCNN | 56.5 | 46.2 | 38.6 | 34 | 27 | 1,697 | 43,147 | 58.8 | 97.3 | 33.6 | 45.1 | 36.2 | 75.1 | 47.2 | 78.1 | 81.0 | 1.1 | 699 | 1,094 |
| MOT17-03-SDP | 70.4 | 48.0 | 41.1 | 65 | 16 | 1,145 | 28,044 | 73.2 | 98.5 | 30.4 | 56.1 | 32.5 | 74.1 | 58.8 | 79.1 | 81.5 | 0.8 | 1,773 | 2,503 |
| MOT17-06-DPM | 39.4 | 36.1 | 28.1 | 18 | 116 | 122 | 6,700 | 43.1 | 97.7 | 25.1 | 31.7 | 30.0 | 56.7 | 32.8 | 74.2 | 78.3 | 0.1 | 314 | 372 |
| MOT17-06-FRCNN | 51.0 | 41.1 | 34.2 | 48 | 60 | 610 | 4,758 | 59.6 | 92.0 | 26.4 | 44.7 | 36.4 | 49.8 | 48.0 | 74.1 | 80.5 | 0.5 | 406 | 340 |
| MOT17-06-SDP | 53.7 | 44.7 | 35.4 | 56 | 67 | 615 | 4,465 | 62.1 | 92.2 | 28.5 | 44.4 | 38.3 | 52.5 | 48.3 | 71.7 | 79.6 | 0.5 | 377 | 328 |
| MOT17-07-DPM | 28.5 | 23.2 | 19.7 | 4 | 32 | 325 | 11,274 | 33.3 | 94.5 | 15.8 | 25.0 | 16.5 | 61.5 | 25.8 | 73.3 | 78.5 | 0.7 | 472 | 641 |
| MOT17-07-FRCNN | 31.2 | 30.0 | 26.5 | 6 | 15 | 1,526 | 9,624 | 43.0 | 82.6 | 23.6 | 31.0 | 25.6 | 58.9 | 34.1 | 65.5 | 77.7 | 3.1 | 473 | 531 |
| MOT17-07-SDP | 42.8 | 29.7 | 26.3 | 11 | 17 | 948 | 8,141 | 51.8 | 90.2 | 18.6 | 37.7 | 20.3 | 60.9 | 40.8 | 71.1 | 79.6 | 1.9 | 581 | 626 |
| MOT17-08-DPM | 23.0 | 21.4 | 20.2 | 5 | 42 | 199 | 15,847 | 25.0 | 96.4 | 20.3 | 20.1 | 21.6 | 68.1 | 20.6 | 79.4 | 82.7 | 0.3 | 229 | 310 |
| MOT17-08-FRCNN | 22.0 | 27.5 | 25.8 | 7 | 39 | 863 | 15,466 | 26.8 | 86.8 | 31.7 | 21.2 | 34.4 | 72.7 | 22.3 | 72.3 | 82.3 | 1.4 | 150 | 200 |
| MOT17-08-SDP | 27.3 | 25.1 | 22.8 | 8 | 34 | 600 | 14,326 | 32.2 | 91.9 | 21.0 | 25.2 | 23.7 | 66.0 | 26.3 | 75.2 | 81.6 | 1.0 | 433 | 535 |
| MOT17-12-DPM | 35.8 | 34.2 | 28.1 | 8 | 48 | 201 | 5,202 | 40.0 | 94.5 | 25.9 | 30.5 | 27.9 | 72.2 | 31.8 | 75.2 | 80.6 | 0.2 | 157 | 232 |
| MOT17-12-FRCNN | 35.1 | 46.2 | 36.9 | 12 | 43 | 717 | 4,817 | 44.4 | 84.3 | 41.7 | 33.0 | 44.4 | 76.0 | 36.3 | 69.0 | 81.2 | 0.8 | 94 | 160 |
| MOT17-12-SDP | 38.0 | 39.5 | 34.0 | 17 | 40 | 765 | 4,407 | 49.2 | 84.8 | 32.0 | 36.3 | 34.6 | 74.5 | 40.3 | 69.5 | 81.9 | 0.9 | 203 | 286 |
| MOT17-14-DPM | 14.2 | 15.6 | 13.7 | 4 | 122 | 271 | 15,213 | 17.7 | 92.3 | 14.1 | 13.4 | 15.7 | 57.7 | 13.7 | 71.5 | 78.7 | 0.4 | 378 | 498 |
| MOT17-14-FRCNN | 15.3 | 25.4 | 21.1 | 10 | 76 | 2,965 | 11,987 | 35.1 | 68.7 | 18.9 | 24.8 | 22.2 | 48.0 | 28.3 | 55.3 | 74.5 | 4.0 | 708 | 740 |
| MOT17-14-SDP | 27.0 | 27.1 | 21.5 | 10 | 62 | 2,002 | 10,599 | 42.7 | 79.7 | 16.2 | 29.4 | 18.4 | 50.6 | 32.9 | 61.6 | 76.9 | 2.7 | 891 | 884 |
Raw data: