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Research map / Detection and segmentation / Tracking

Fast Online Object Tracking and Segmentation: A Unifying Approach

CVPR 2019 · Detection and segmentation › Tracking · approach: Siamese network tracking · 1,541 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add a segmentation mask branch and train it jointly with similarity and box prediction (ablation)SiamRPN · VOT-2018EAO: 0.359 -> 0.380Helped
Add a segmentation mask branch to SiamFC, without box regression (ablation)SiamFC · VOT-2018EAO: 0.251 to 0.265Helped
Use the mask branch rather than the box branch to generate boxes (ablation)SiamMask · VOT-2018EAO: 0.363 -> 0.380Helped
Use a rotated minimum bounding rectangle rather than an axis-aligned Min-max box (ablation)SiamMask · VOT-2016 random cropsmAP@0.7 IOUHelped
Use Opt box generation instead of MBR (ablation)SiamMask · VOT-2018EAO: 0.380 -> 0.387Helped
Use Opt box generation instead of MBR (ablation)SiamMask · VOT-2018Speed: 55 to 5Hurt
Remove the box regression branch (ablation)SiamMask · VOT-2018EAO: 0.380 -> 0.334Hurt
Remove the mask refinement modules (ablation)SiamMask · DAVIS-2016 validationF mean: 67.8 -> 57.8Hurt
Replace AlexNet with ResNet-50 as the shared backbone (ablation)SiamRPN · VOT-2018EAO: 0.243 -> 0.359Helped
Use MBR mask-derived boxes rather than axis-aligned box representation (ablation)SiamMask · VOT-2016 random cropsmAP@0.5 IOU: +29 and +9.2 pointsHelped

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