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Learning Attribute Representations With Localization for Flexible Fashion Search

CVPR 2018 · Label-efficient and robust learning › Recognition and long-tail · approach: Correspondence and causal representation learning · 130 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add attribute localization with AAMs and ROI pooling (ablation)FashionSearchNet · Shopping100k, query + attribute manipulationTop-30 retrieval accuracy: 5.4% higher than the nearest competitorHelped
Add attribute localization with AAMs and ROI pooling (ablation)FashionSearchNet · DeepFashion, query + attribute manipulationTop-30 retrieval accuracy: 6.3% higher than the nearest competitorHelped
Use FashionSearchNet instead of AMNetShopping100k, query + attribute manipulation · Shopping100kTop-30 retrieval accuracy: 16% better than AMNetHelped
Use FashionSearchNet instead of AMNetDeepFashion, query + attribute manipulation · DeepFashionTop-30 retrieval accuracy: 13% better than AMNetHelped
Add region awareness and region-specific attribute representationsFashionSearchNet · Shopping100k, region-specific color manipulation user studySuccess rate: 8.6% -> 22.2%Helped
Use FashionSearchNet instead of AMNetShopping100k, region-specific color manipulation user study · Shopping100kSuccess rate: 1.2% -> 8.6%Helped

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