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Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification

CVPR 2020 · Label-efficient and robust learning › Recognition and long-tail · approach: Cross-modality and occlusion re-identification · 370 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use hierarchical cross-modality disentanglement with ID-PIG and HFLVI-ReID · RegDBRank-1: 50.85 -> 70.93Helped
Use hierarchical cross-modality disentanglement with ID-PIG and HFLVI-ReID · SYSU-MM01Rank-1: 28.90 -> 34.94Helped
Add alternate sampling of original and cross-reconstructed features (ablation)HFL with CE+TRIP and A+P features · RegDBRank-1: 53.25 -> 70.93Helped
Add alternate sampling of original and cross-reconstructed features (ablation)HFL with CE+TRIP and A+P features · SYSU-MM01mAP: 30.53 -> 35.94Helped
Combine style-attribute and prototype codes rather than using style-attribute code alone (ablation)HFL on original images with CE+TRIP · RegDBRank-1: 15.33 -> 53.25Helped
Combine style-attribute and prototype codes rather than using prototype code alone (ablation)HFL on original images with CE+TRIP · SYSU-MM01Rank-1: 22.51 -> 29.19Helped
Remove same-modality reconstruction loss (ablation)ID-PIG · RegDB and SYSU-MM01 image translationvisual image qualityHurt
Remove cross-modality reconstruction loss (ablation)ID-PIG · RegDB and SYSU-MM01 image translationvisual image qualityHurt
Remove adversarial loss (ablation)ID-PIG · RegDB and SYSU-MM01 image translationvisual image qualityHurt

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