CVJun 27, 2023
UniUD Submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2023
arXiv:2306.15445v2h-index: 7
AI Analysis
This is an incremental submission to a domain-specific challenge in video retrieval.
The authors tackled the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge by ensembling two models trained on limited data, achieving an average score of 56.81% nDCG and 42.63% mAP.
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.