Visual Object Tracking On Tnl2K
Métriques
AUC
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | AUC |
|---|---|
| exploring-enhanced-contextual-information-for-1 | 62.9 |
| rtracker-recoverable-tracking-via-pn-tree | 60.6 |
| Modèle 3 | 57.4 |
| tracking-meets-lora-faster-training-larger | 62.7 |
| exploring-enhanced-contextual-information-for-1 | 65.3 |
| artrackv2-prompting-autoregressive-tracker | 61.6 |
| seqtrack-sequence-to-sequence-learning-for | 57.8 |
| towards-more-flexible-and-accurate-object | - |
| odtrack-online-dense-temporal-token-learning | 60.9 |
| autoregressive-visual-tracking | 60.3 |
| odtrack-online-dense-temporal-token-learning | 61.7 |
| dropmae-masked-autoencoders-with-spatial | 56.9 |
| tracking-meets-lora-faster-training-larger | 62.3 |