Benchmark:
Short name:
AMIR3D
Detector:
Public
Description:
n/a
Reference:
A. Sadeghian, A. Alahi, S. Savarese. Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies. In ICCV, 2017.
Last submitted:
September 02, 2016 (8 years ago)
Published:
January 16, 2017 at 02:35:43 CET
Submissions:
2
Project page / code:
Open source:
No
Hardware:
3.5 Ghz, 8 cores
Runtime:
1.2 Hz
Benchmark performance:
Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
3D MOT 2015 | 25.0 | 0.0 | 0.0 | 8 (3.0) | 74 (27.6) | 2,038 | 9,084 | 45.9 | 79.1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.3 | 1,462 (31.9) | 1,647 (35.9) |
Detailed performance:
Sequence | MOTA | IDF1 | HOTA | MT | ML | FP | FN | Rcll | Prcn | AssA | DetA | AssRe | AssPr | DetRe | DetPr | LocA | FAF | ID Sw. | Frag |
AVG-TownCentre | 14.8 | 0.0 | 0.0 | 22 | 42 | 1,768 | 3,515 | 50.8 | 67.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.9 | 805 | 732 |
PETS09-S2L2 | 33.8 | 0.0 | 0.0 | 5 | 2 | 1,380 | 3,945 | 59.1 | 80.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.2 | 1,062 | 902 |
Raw data: