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Research map / Label-efficient and robust learning / Recognition and long-tail

Context-Aware Correlation Filter Tracking

CVPR 2017 · Label-efficient and robust learning › Recognition and long-tail · approach: Dense features and foundation priors · 666 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add context patches as a regularizer to MOSSEMOSSE · OTB-100precision: 0.414 -> 0.598Helped
Add context patches as a regularizer to MOSSEMOSSE · OTB-100success: 0.311 -> 0.447Helped
Add context patches as a regularizer to DCFDCF · OTB-100precision: 0.690 -> 0.744Helped
Add context patches as a regularizer to DCFDCF · OTB-100success: 0.475 -> 0.511Helped
Add context patches as a regularizer to SAMFSAMF · OTB-100precision: 0.743 -> 0.793Helped
Add context patches as a regularizer to SAMFSAMF · OTB-100success: 0.535 -> 0.575Helped
Add context patches as a regularizer to STAPLESTAPLE · OTB-100precision: 0.784 -> 0.810Helped
Add context patches as a regularizer to STAPLESTAPLE · OTB-100success: 0.579 -> 0.598Helped
Use context patches instead of the target-adaptive framework with SAMFSAMF · OTB-100success: 0.549 -> 0.575Helped
Use context patches instead of the target-adaptive framework with DCFDCF · OTB-100success: 0.504 -> 0.511Helped
Use context patches instead of the target-adaptive framework with MOSSEMOSSE · OTB-100success: 0.413 -> 0.447Helped

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