HyperAI

Multiple Object Tracking On Sportsmot

المقاييس

AssA
DetA
HOTA
IDF1
MOTA

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

جدول المقارنة
اسم النموذجAssADetAHOTAIDF1MOTA
gta-global-tracklet-association-for-multi74.588.281.086.596.3
a-simple-baseline-for-multi-object-tracking34.770.249.353.586.4
sportsmot-a-large-multi-object-tracking54.878.865.774.196.2
quasi-dense-instance-similarity-learning47.277.560.462.390.1
sportsmot-a-large-multi-object-tracking62.088.574.174.496.5
multiple-object-tracking-as-id-prediction65.486.575.278.296.1
engineering-an-efficient-object-tracker-for-170.388.178.781.796.5
associate-everything-detected-facilitating70.189.479.181.897.1
beyond-kalman-filters-deep-learning-based63.787.574.676.996.7
deep-hm-sort-enhancing-multi-object-tracking72.788.380.185.296.6
exploring-learning-based-motion-models-in58.686.771.371.194.9
bytetrack-multi-object-tracking-by-152.378.564.171.495.9
memotr-long-term-memory-augmented-transformer59.183.170.071.491.5
tracking-objects-as-points48.082.162.760.090.8
multiple-object-tracking-as-id-prediction62.083.471.975.092.9
iterative-scale-up-expansioniou-and-deep67.788.277.279.896.3
observation-centric-sort-rethinking-sort-for61.588.573.774.096.5
memotr-long-term-memory-augmented-transformer57.882.068.869.990.2