Paper ID: 2306.15445

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

Alex Falcon, Giuseppe Serra

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.

Submitted: Jun 27, 2023