MOT20Det Results
Click on a measure to sort the table accordingly. See below for a more detailed description.
| Tracker | AP | MODA | MODP | FAF | TP | FP | FN | Rcll | Prcn | F1 | Hz |
| AliDet 1. |
0.90 ±0.06 |
76.3 ±18.6 | 81.7 | 13.1 | 320,830 | 58,629 | 22,694 | 93.4 | 84.5 | 88.8 | 16.9 |
| Bresee_Det 2. |
0.87 ±0.09 |
35.6 ±45.8 | 73.3 | 42.6 | 313,100 | 190,776 | 30,424 | 91.1 | 62.1 | 73.9 | 11.2 |
| DeDeT 3. |
0.87 ±0.09 |
36.9 ±38.9 | 81.7 | 42.5 | 317,196 | 190,472 | 26,328 | 92.3 | 62.5 | 74.5 | 16.9 |
| GNN_SDT 4. |
0.81 ±0.09 |
79.3 ±15.1 | 80.0 | 7.1 | 304,236 | 31,677 | 39,288 | 88.6 | 90.6 | 89.6 | 1.2 |
| Y. Wang, X. Weng, K. Kitani. Joint Detection and Multi-Object Tracking with Graph Neural Networks. In arXiv, 2020. | |||||||||||
| ViPeD20 5. |
0.80 ±0.07 |
46.0 ±40.5 | 79.0 | 31.1 | 297,101 | 139,111 | 46,277 | 86.5 | 68.1 | 76.2 | 11.2 |
| L. Ciampi, N. Messina, F. Falchi, C. Gennaro, G. Amato. Virtual to Real Adaptation of Pedestrian Detectors. In Sensors, 2020. | |||||||||||
| Sequences | Frames | Trajectories | Boxes |
| 4 | 4479 | 1501 | 765465 |
Difficulty Analysis
Sequence difficulty (from easiest to hardest, measured by average AP)
MOT20-04
(0.88 AP)
MOT20-07
(0.88 AP)
MOT20-08
(0.74 AP)
MOT20-06
(0.72 AP)
Evaluation Measures
Lower is better. Higher is better.| Measure | Better | Perfect | Description |
| AP | higher | 1 | Average Precision taken over a set of reference recall values (0:0.1:1) |
| MODA | higher | 100% | Multi-Object Detection Accuracy [1]. This measure combines false positives and missed targets. |
| MODP | higher | 100% | Multi-Object Detection Precision [1]. The misalignment between the annotated and the predicted bounding boxes. |
| FAF | lower | 0 | The average number of false alarms per frame. |
| TP | higher | #GT | The total number of true positives. |
| FP | lower | 0 | The total number of false positives. |
| FN | lower | 0 | The total number of false negatives (missed targets). |
| Rcll | higher | 100% | Ratio of correct detections to total number of GT boxes. |
| Prcn | higher | 100% | Ratio of TP / (TP+FP). |
| F1 | higher | 100% | Harmonic mean of precision and recall. |
| Hz | higher | Inf. | Processing speed (in frames per second excluding the detector) on the benchmark. The frequency is provided by the authors and not officially evaluated by the MOTChallenge. |
Legend
| Symbol | Description |
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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. |
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This method used the provided detection set as input. |
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This method used a private detection set as input. |
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This entry has been submitted or updated less than a week ago. |
References:
| [1] | Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics. Image and Video Processing, 2008(1):1-10, 2008. |
