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Research map / Detection and segmentation / Open-set and few-shot detection

Primary Object Segmentation in Videos Based on Region Augmentation and Reduction

CVPR 2017 · Detection and segmentation › Open-set and few-shot detection · approach: Unsupervised object and part discovery · 196 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add iterative augmentation and reduction refinement to initial regions (ablation)Primary object segmentation · DAVISJ Mean: 0.719 -> 0.763Helped
Add iterative augmentation and reduction refinement to initial regions (ablation)Primary object segmentation · DAVISF Mean: 0.680 -> 0.711Helped
Replace ARP with GMM-based refinement [20] (ablation)Initial primary object regions · DAVISJ Mean: 0.719 -> 0.580Hurt
Replace ARP with GMM-based refinement [36] (ablation)Initial primary object regions · DAVISJ Mean: 0.719 -> 0.670Hurt
Use ARP instead of GMM-based refinement (ablation)Primary object segmentation · DAVISJ Mean: 0.580 -> 0.763Helped
Use ARP instead of GMM-based refinement (ablation)Primary object segmentation · DAVISJ Mean: 0.670 -> 0.763Helped
Use ARP rather than the strongest listed baselinePrimary object segmentation · DAVISJ Mean: 0.665 -> 0.763Helped
Use the proposed segmentation algorithm rather than [20]Primary object segmentation · FBMS testAverage IoU: 0.555 -> 0.598Helped

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