PS:结果是由foolwood维护的
Benchmark Results
The trackers are ordered by the average overlap scores.
-
AUCandPrecisionare the standard metrics. -
Deep Learning: deep learning features, deep learning method and RL. -
RealTime: Speeds from the original paper, not test on the same platform. (just focus magnitude)
| Tracker | AUC-CVPR2013 | Precision-CVPR2013 | AUC-OTB100 | Precision-OTB100 | AUC-OTB50 | Precision-OTB50 | Deep Learning | RealTime |
|---|---|---|---|---|---|---|---|---|
| ECO | 0.709 | 0.93 | 0.694 | 0.910 | 0.643 | 0.874 | Y | N(6) |
| MDNet | 0.708 | 0.948 | 0.678 | 0.909 | 0.645 | 0.890 | Y | N(1) |
| SANet | 0.686 | 0.95 | 0.692 | 0.928 | - | - | Y | N(1) |
| BranchOut | 0.678 | 0.917 | Y | N(1) | ||||
| TCNN | 0.682 | 0.937 | 0.654 | 0.884 | - | - | Y | N(1) |
| TSN | 0.644 | 0.868 | 0.58 | 0.809 | Y | N(1) | ||
| CRT | - | - | 0.642 | 0.875 | 0.594 | 0.835 | Y | N(1.3) |
| BACF | 0.678 | 0.63 | N | Y(35) | ||||
| MCPF | 0.677 | 0.916 | 0.628 | 0.873 | Y | N(0.5) | ||
| CREST | 0.673 | 0.908 | 0.623 | 0.837 | - | - | Y | N(1) |
| C-COT | 0.672 | 0.899 | 0.682 | - | - | - | Y | N(0.3) |
| DNT | 0.664 | 0.907 | 0.627 | 0.851 | - | - | Y | N(5) |
| PTAV | 0.663 | 0.894 | 0.635 | 0.849 | Y | Y(25) | ||
| ADNet | 0.659 | 0.903 | 0.646 | 0.88 | Y | N(3) | ||
| DSiamM | 0.656 | 0.891 | Y | Y(25) | ||||
| SINT+ | 0.655 | 0.882 | - | - | - | - | Y | N(4) |
| DRT | 0.655 | 0.892 | - | - | - | - | Y | N(0.8) |
| RDT | 0.654 | - | 0.603 | - | - | - | Y | Y(43) |
| SRDCFdecon | 0.653 | 0.87 | 0.627 | 0.825 | 0.56 | 0.764 | N | N(1) |
| DeepLMCF | 0.643 | 0.892 | Y | N(8) | ||||
| MUSTer | 0.641 | 0.865 | 0.575 | 0.774 | - | - | N | N(4) |
| DeepSRDCF | 0.641 | 0.849 | 0.635 | 0.851 | 0.56 | 0.772 | Y | N(<1) |
| EAST | 0.638 | Y | Y(23/159) | |||||
| SINT | 0.635 | 0.851 | - | - | - | - | Y | N(4) |
| LCT | 0.628 | 0.848 | 0.562 | 0.762 | 0.492 | 0.691 | N | Y(27) |
| SRDCF | 0.626 | 0.838 | 0.598 | 0.789 | 0.539 | 0.732 | N | N(5) |
| LMCF | 0.624 | 0.839 | 0.568 | N | Y(85) | |||
| SCF | 0.623 | 0.874 | - | - | - | - | N | Y(35) |
| Staple_CA | 0.621 | 0.833 | 0.598 | 0.81 | N | Y(35) | ||
| RaF | 0.615 | 0.919 | Y | N(2) | ||||
| SiamFC | 0.612 | 0.815 | - | - | - | - | Y | Y(58) |
| RFL | 0.581 | Y | Y(15) | |||||
| CFNet_conv2 | 0.611 | 0.807 | 0.568 | 0.748 | 0.53 | 0.702 | Y | Y(75) |
| SiamFC_{3s} | 0.608 | 0.809 | - | - | - | - | Y | Y(86) |
| ACFN | 0.607 | 0.86 | 0.575 | 0.802 | Y | Y(15) | ||
| CF2 | 0.605 | 0.891 | 0.562 | 0.837 | 0.513 | 0.803 | Y | N(11) |
| HDT | 0.603 | 0.889 | 0.654 | 0.848 | 0.515 | 0.804 | Y | N(10) |
| Staple | 0.6 | 0.793 | 0.578 | 0.784 | - | - | N | Y(80) |
| CSR-DCF | 0.599 | 0.8 | 0.598 | 0.733 | N | Y(13) | ||
| FCNT | 0.599 | 0.856 | - | - | - | - | Y | N(1) |
| CNN-SVM | 0.597 | 0.852 | 0.554 | 0.814 | 0.512 | 0.769 | Y | N |
| SCT | 0.595 | 0.845 | - | - | - | - | Y | Y(40) |
| SO-DLT | 0.595 | 0.81 | - | - | - | - | Y | N |
| BIT | 0.593 | 0.817 | - | - | - | - | N | Y(45) |
| DLSSVM | 0.589 | 0.829 | 0.541 | 0.767 | - | - | Y | N(10) |
| SAMF | 0.579 | 0.785 | 0.535 | 0.743 | - | - | N | N(7) |
| RPT | 0.577 | 0.805 | - | - | - | - | N | N(4) |
| MEEM | 0.566 | 0.83 | 0.53 | 0.781 | 0.473 | 0.712 | N | N(10) |
| DSST | 0.554 | 0.737 | 0.52 | 0.693 | 0.463 | 0.625 | N | Y(24) |
| CNT | 0.545 | 0.723 | - | - | - | - | Y | N(1.5) |
| TGPR | 0.529 | 0.766 | 0.458 | 0.643 | - | - | N | N(1) |
| KCF | 0.514 | 0.74 | 0.477 | 0.693 | 0.403 | 0.611 | N | Y(172) |
| GOTURN | 0.444 | 0.62 | 0.427 | 0.572 | - | - | Y | Y(165) |