Multi Object Tracking On Mot20 1
Metrics
IDF1
MOTA
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | IDF1 | MOTA |
|---|---|---|
| 2103-15145 | 57.9 | 72.4 |
| bot-sort-robust-associations-multi-pedestrian | 77.5 | 77.8 |
| adaptrack-adaptive-thresholding-based | 80.7 | 75.0 |
| boosttrack-boosting-the-similarity-measure | 81.5 | 77.2 |
| simpletrack-rethinking-and-improving-the-jde | 70.2 | 72.6 |
| ucmctrack-multi-object-tracking-with-uniform | 77.4 | - |
| spatial-temporal-graph-transformer-for | 75.2 | 77.5 |
| multiple-object-tracking-from-appearance-by | 69.7 | 68.0 |
| joint-detection-and-multi-object-tracking | - | 67.1 |
| interacting-multiple-model-based-joint | 74.64 | 72.82 |
| a-confidence-aware-matching-strategy-for | 79.9 | 76.2 |
| deep-oc-sort-multi-pedestrian-tracking-by | 79.2 | 75.6 |
| learning-a-neural-solver-for-multiple-object-1 | 59.1 | 57.6 |
| boosttrack-using-tracklet-information-to | 82 | 77.7 |
| bytetrack-multi-object-tracking-by-1 | 75.2 | 77.8 |
| online-multi-object-tracking-with | 69.4 | 68.5 |
| sparsetrack-multi-object-tracking-by | 77.3 | 78.2 |
| detection-recovery-in-online-multi-object | 70.6 | 72.8 |
| hoptrack-a-real-time-multi-object-tracking | - | 45.6 |
| lmot-efficient-light-weight-detection-and | 61.1 | 59.1 |
| a-simple-baseline-for-multi-object-tracking | 67.3 | 61.8 |
| strongsort-make-deepsort-great-again | 77.0 | 73.8 |
| smiletrack-similarity-learning-for-multiple | 77.5 | 78.2 |
| observation-centric-sort-rethinking-sort-for | 76.4 | 75.9 |
| sfsort-scene-features-based-simple-online | 73.5 | 75 |
| when-to-extract-reid-features-a-selective | 75.4 | - |