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Research map / 3D vision / Depth and stereo

Optimal Feature Transport for Cross-View Image Geo-Localization

AAAI 2020 · 3D vision › Depth and stereo · approach: Scene coordinate regression for localization · 171 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add CVFT feature transport (ablation)Our network · CVUSAr@1: 41.68 -> 61.43Helped
add CVFT feature transport (ablation)Our network · CVACT_valr@1: 45.28 -> 61.05Helped
preserve local spatial feature layout instead of global max pooling (ablation)VGG16 cross-view localization network · CVUSAr@1: 31.53 -> 61.43Helped
preserve local spatial feature layout instead of global max pooling (ablation)VGG16 cross-view localization network · CVACT_valr@1: 28.98 -> 61.05Helped
add ±20° orientation noise (ablation)Our network · CVUSAr@1: 61.43 -> 52.07Hurt
add ±20° orientation noise (ablation)Our network · CVACT_valr@1: 61.05 -> 54.81Hurt
replace CVFT with 2D-affine STN (ablation)Our network · CVUSAr@1: 61.43 -> 37.29Hurt
replace CVFT with 2D-affine STN (ablation)Our network · CVACT_valr@1: 61.05 -> 35.64Hurt
replace CVFT with thin-plate-spline STN (ablation)Our network · CVUSAr@1: 61.43 -> 42.38Hurt
replace CVFT with thin-plate-spline STN (ablation)Our network · CVACT_valr@1: 61.05 -> 41.61Hurt
reduce embedding dimension to 2048 (ablation)CVFT · CVUSAr@1: 61.43 -> 56.43Hurt
reduce embedding dimension to 2048 (ablation)CVFT · CVACT_valr@1: 61.05 -> 57.86Hurt

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