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Composed Query Image Retrieval Using Locally Bounded Features

CVPR 2020 · Image generation › Autoregressive and latent generation · approach: Retrieval and matching with generative features · 82 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
represent images as local regions and correlate text words with image regionscomposed query image retrieval · Fashion200KRecall@1: 14.1±0.6 -> 17.78±0.5Helped
represent images as local regions and correlate text words with image regionscomposed query image retrieval · MIT StatesRecall@1: 12.3±0.5 -> 14.72±0.6Helped
represent images as local regions and correlate text words with image regionscomposed query image retrieval · CSS 3D→3DRecall@1: 73.7±1.0 -> 79.2±1.2Helped
represent images as local regions and correlate text words with image regionscomposed query image retrieval · CSS 2D→3DRecall@1: 46.6 -> 55.69±0.9Helped
add the auxiliary loss LB during training (ablation)proposed method · CSS 3DRecall@1: 76.1 -> 79.2Helped
use 36 rather than 18 region proposals (ablation)proposed method · Fashion200KRecall@1: 16.26±0.6 -> 17.78±0.5Helped
use 36 rather than 18 region proposals (ablation)proposed method · MIT StatesRecall@1: 14.29±0.6 -> 14.72±0.6Helped
use 36 rather than 18 region proposals (ablation)proposed method · CSS 3D→3DRecall@1: 67.26±1.1 -> 79.2±1.2Helped
use coarse filtering with θ = 100 (ablation)proposed method at inference · CSS 3DRecall@1: 79.2 -> 75.92Hurt
use coarse filtering with θ = 100 (ablation)proposed method at inference · CSS 3DACRR: 75.24%Helped
use coarse filtering with θ = 85 (ablation)proposed method at inference · CSS 3DRecall@1: 79.2 -> 70.81Hurt
use coarse filtering with θ = 85 (ablation)proposed method at inference · CSS 3DACRR: 91.86%Helped

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