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

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