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UniUD Submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2023

2023/06/27 by Falcon, Alex, Serra, Giuseppe
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.2306.15445

Abstract

In this report, we present the technical details of our submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2023. To participate in the challenge, we ensembled two models trained with two different loss functions on 25% of the training data. Our submission, visible on the public leaderboard, obtains an average score of 56.81% nDCG and 42.63% mAP.

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