Visual Object Tracking On Otb 2013
평가 지표
AUC
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | AUC | Paper Title | Repository |
|---|---|---|---|
| SiamVGG | 0.665 | SiamVGG: Visual Tracking using Deeper Siamese Networks | - |
| DSiam | 0.656 | Learning Dynamic Siamese Network for Visual Object Tracking | - |
| SE-SiamFC | 0.68 | Scale Equivariance Improves Siamese Tracking | - |
| CFNet | 0.611 | End-to-end representation learning for Correlation Filter based tracking | - |
| SA-Siam | 0.677 | A Twofold Siamese Network for Real-Time Object Tracking | - |
| RASNet | 0.670 | Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking | - |
| SiamFC-3s | 0.607 | Fully-Convolutional Siamese Networks for Object Tracking | - |
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