Research map / Label-efficient and robust learning / Recognition and long-tail
Multi-Cue Correlation Filters for Robust Visual Tracking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| combine multiple expert predictions with robustness-based expert selection (ablation) | MCCT · OTB-2015 | DP (@20px): 87.1 -> 88.3 | Helped |
| add adaptive update based on expert divergence and PSR (ablation) | MCCT · OTB-2015 | DP (@20px): 88.3 -> 91.4 | Helped |
| add adaptive update based on expert divergence and PSR (ablation) | MCCT-H · OTB-2013 | DP (@20px): 83.5 -> 85.6 | Helped |
| replace the proposed reliability score with PSR-based sample reliability (ablation) | MCCT · OTB-2013 | DP (@20px): 91.9 -> 90.9 | Hurt |
| replace the proposed reliability score with PSR-based sample reliability (ablation) | MCCT-H · OTB-2015 | DP (@20px): 83.3 -> 82.7 | Hurt |
| use multiple experts and select the most robust prediction instead of relying on one expert (ablation) | MCCT · OTB-2013 | DP (@20px): 89.7 -> 92.8 | Helped |
| use multiple experts and select the most robust prediction instead of relying on one expert (ablation) | MCCT-H · OTB-2015 | DP (@20px): 79.2 -> 84.1 | Helped |
Closest papers by meaning
- Correlation Tracking via Joint Discrimination and Reliability Learning (CVPR 2018 · similarity 0.90)
- Structural Correlation Filter for Robust Visual Tracking (CVPR 2016 · similarity 0.89)
- Multi-Task Correlation Particle Filter for Robust Object Tracking (CVPR 2017 · similarity 0.89)
- ECO: Efficient Convolution Operators for Tracking (CVPR 2017 · similarity 0.89)
- Correlation-Aware Deep Tracking (CVPR 2022 · similarity 0.89)
- Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking (CVPR 2018 · similarity 0.88)
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