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

Learning Unsupervised Video Object Segmentation Through Visual Attention

CVPR 2019 · Detection and segmentation › Open-set and few-shot detection · approach: Unsupervised object and part discovery · 254 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the attention-guided UVOS model instead of PDBUVOS on DAVIS16 · DAVIS16 testJ Mean: 77.2 -> 79.7Helped
Use the attention-guided UVOS model instead of PDBUVOS on DAVIS16 · DAVIS16 testF Mean: 74.5 -> 77.4Helped
Use the attention-guided UVOS model instead of LVOUVOS on DAVIS16 · DAVIS16 testT Mean: 26.5 -> 44.5Hurt
Use the attention-guided UVOS model instead of LVOUVOS on Youtube-Objects · Youtube-ObjectsJ Mean: 67.5 -> 69.7Helped
Use the attention-guided model instead of PDBVSOD on DAVIS16 · DAVIS16 testF max: 0.849 -> 0.870Helped
Use the attention-guided model instead of PDBVSOD on DAVIS16 · DAVIS16 testMAE: 0.030 -> 0.026Helped
Use UVOS-aware DVAP instead of ACLVisual attention prediction on DAVIS16 · DAVIS16 attention testSIM: 0.453 -> 0.504Helped
Use UVOS-aware DVAP instead of ACLVisual attention prediction on Youtube-Objects · Youtube-Objects attention testSIM: 0.405 -> 0.419Helped

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