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X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval

CVPR 2022 · Video › Video-language understanding · approach: Text-video retrieval · 223 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace text-agnostic frame pooling with text-conditioned cross-modal attentionCLIP-based text-video retrieval · MSR-VTT-9KR@1: 44.5 -> 46.9Helped
replace text-agnostic frame pooling with text-conditioned cross-modal attentionCLIP-based text-video retrieval · MSR-VTT-7KR@1: 42.1 -> 43.9Helped
replace text-agnostic frame pooling with text-conditioned cross-modal attentionCLIP-based text-video retrieval · MSVDR@1: 46.2 -> 47.2Helped
replace text-agnostic frame pooling with text-conditioned cross-modal attentionCLIP-based text-video retrieval · LSMDCR@1: 22.6 -> 25.2Helped
add text-conditioned top-k frame pooling instead of mean-pooling (ablation)CLIP retrieval on MSR-VTT · MSR-VTTR@1: up to 6% relative improvementHelped
increase scene transitions in videosmean-pooling retrieval · MSR-VTT augmented test setMedian Rank: 2 to 46Hurt
increase scene transitions in videosX-Pool retrieval · MSR-VTT augmented test setMedian Rank: 2 to 9Hurt
use 6 sampled frames rather than the default 12 (ablation)X-Pool · MSR-VTT-9KR@1Hurt

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