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Learning Action Changes by Measuring Verb-Adverb Textual Relationships

CVPR 2023 · Video › Action recognition · approach: Action anticipation and latent actions · 6 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use verb-adverb textual relationships as regression targets instead of fixed δ (ablation)REG · HowTo100M AdverbsmAP W: 0.320 -> 0.555Helped
Use verb-adverb textual relationships as regression targets instead of fixed δ (ablation)REG · Adverbs in RecipesmAP W: 0.554 -> 0.613Helped
Use verb-adverb textual relationships as regression targets instead of fixed δ (ablation)REG · ActivityNet AdverbsmAP W: 0.115 -> 0.119No clear effect
Use verb-adverb textual relationships as regression targets instead of fixed δ (ablation)REG · MSR-VTT AdverbsmAP W: 0.203 -> 0.282Helped
Use verb-adverb textual relationships as regression targets instead of fixed δ (ablation)REG · VATEX AdverbsmAP W: 0.175 -> 0.261Helped
Use regression rather than classification (ablation)Adverbs in Recipes · Adverbs in RecipesmAP W: 0.606 -> 0.613Helped
Use regression rather than classification (ablation)HowTo100M Adverbs · HowTo100M AdverbsmAP M: 0.420 -> 0.423No clear effect
Remove action labels at test timeREG · Adverbs in RecipesmAP W: 0.613 -> 0.520Hurt
Train without antonym pairings (ablation)REG · Adverbs in RecipesmAP W: 0.613 -> 0.667Helped
Train without antonym pairings (ablation)REG · HowTo100M AdverbsmAP M: 0.423 -> 0.481Helped
Add an MLP to Action Modifiers (ablation)Action Modifiers · HowTo100M AdverbsmAP W: 0.406 -> 0.279Hurt
Add an MLP to Action Modifiers (ablation)Action Modifiers · Adverbs in RecipesAcc-A: 0.857 -> 0.860No clear effect

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