Visual Object Tracking On Lasot
評価指標
AUC
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
比較表
| モデル名 | AUC |
|---|---|
| a-distractor-aware-memory-for-visual-object | 75.1 |
| universal-instance-perception-as-object | 72.4 |
| tracking-meets-lora-faster-training-larger | 75.1 |
| neighbortrack-improving-single-object | 72.2 |
| 2103-15436 | 64.9 |
| learning-to-fuse-asymmetric-feature-maps-in | 57.2 |
| aiatrack-attention-in-attention-for | 69.0 |
| improving-visual-object-tracking-through | 73.4 |
| how-to-train-your-energy-based-model-for | 63.7 |
| transforming-model-prediction-for-tracking | - |
| mixformer-end-to-end-tracking-with-iterative-1 | 70.1 |
| learning-spatio-temporal-transformer-for | 67.1 |
| exploring-enhanced-contextual-information-for-1 | 76.6 |
| towards-grand-unification-of-object-tracking | 68.5 |
| learning-historical-status-prompt-for | 72.7 |
| odtrack-online-dense-temporal-token-learning | 73.2 |
| artrackv2-prompting-autoregressive-tracker | 73.6 |
| mixformer-end-to-end-tracking-with-iterative-2 | 73.3 |
| モデル 19 | 70.6 |
| learning-target-candidate-association-to-keep | 67.1 |
| autoregressive-visual-tracking | 73.1 |
| siam-r-cnn-visual-tracking-by-re-detection | 64.8 |
| odtrack-online-dense-temporal-token-learning | 74.0 |
| dropmae-masked-autoencoders-with-spatial | 71.8 |
| samurai-adapting-segment-anything-model-for-1 | 74.2 |
| towards-sequence-level-training-for-visual | 66.8 |
| atom-accurate-tracking-by-overlap | 51.4 |
| revealing-the-dark-secrets-of-masked-image | 70 |
| 190407220 | - |
| rtracker-recoverable-tracking-via-pn-tree | 74.7 |
| swintrack-a-simple-and-strong-baseline-for | 70.2 |
| transformer-meets-tracker-exploiting-temporal | 63.7 |
| tracking-meets-lora-faster-training-larger | 76.2 |
| revealing-the-dark-secrets-of-masked-image | 70.7 |
| exploring-enhanced-contextual-information-for-1 | 75.3 |
| a-distilled-model-for-tracking-and-tracker | 57.6 |
| target-aware-tracking-with-long-term-context | 71.1 |
| loretrack-efficient-and-accurate-low | 70.3 |
| seqtrack-sequence-to-sequence-learning-for | 72.5 |
| 190407220 | 56.8 |
| universal-instance-perception-as-object | 72.2 |
| integrating-boxes-and-masks-a-multi-object | 72.0 |
| joint-feature-learning-and-relation-modeling | 71.1 |