Research map / Detection and segmentation / Tracking
Discriminative Correlation Filter With Channel and Spatial Reliability
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add adaptive channel reliability weights to filter responses (ablation) | CSR-DCF · VOT2016 | EAO: 0.297 -> 0.338; 12% performance drop | Helped |
| add an adaptive spatial reliability map instead of a uniform bounding-box map (ablation) | CSR-DCF · VOT2016 | EAO: 0.264 -> 0.338; 21% drop | Helped |
| add adaptive channel weights and spatial reliability map (ablation) | CSR-DCF · VOT2016 | EAO: 0.256 -> 0.338; 24% drop | Helped |
| add channel and spatial reliability maps (ablation) | standard DCF · VOT2016 | EAO: 0.152 -> 0.338; over 50% drop when removed | Helped |
| use spatial-reliability boundary constraints rather than spatial regularization or limited boundaries | HOG-based correlation filter · VOT2015 | AUC: 0.28 -> 0.32; 0.16 -> 0.32 | Helped |
Closest papers by meaning
- Correlation Tracking via Joint Discrimination and Reliability Learning (CVPR 2018 · similarity 0.90)
- ECO: Efficient Convolution Operators for Tracking (CVPR 2017 · similarity 0.89)
- Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking (CVPR 2018 · similarity 0.88)
- Multi-Cue Correlation Filters for Robust Visual Tracking (CVPR 2018 · similarity 0.87)
- Structural Correlation Filter for Robust Visual Tracking (CVPR 2016 · similarity 0.87)
- Visual Tracking via Adaptive Spatially-Regularized Correlation Filters (CVPR 2019 · similarity 0.86)
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