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In this report, we present our approach for EPIC-KITCHENS-100 Multi-InstanceRetrieval Challenge 2022. We first parse sentences into semantic rolescorresponding to verbs and nouns; then utilize self-attentions to exploitsemantic role contextualized video features along with textual features viatriplet losses in multiple embedding spaces. Our method overpasses the strongbaseline in normalized Discounted Cumulative Gain (nDCG), which is morevaluable for semantic similarity. Our submission is ranked 3rd for nDCG andranked 4th for mAP.

Exploiting Semantic Role Contextualized Video Features for  Multi-Instance Text-Video Retrieval EPIC-KITCHENS-100 Multi-Instance  Retrieval Challenge 2022