2nd Place Solution to Google Universal Image Embedding

Autor:	Huang, Xiaolong, Li, Qiankun
Rok vydání:	2022
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	Image representations are a critical building block of computer vision applications. This paper presents the 2nd place solution to the Google Universal Image Embedding Competition, which is part of the ECCV2022 instance-level recognition workshops. We use the instance-level fine-grained image classification method to complete this competition. We focus on data building and processing, model structure, and training strategies. Finally, the solution scored 0.713 on the public leaderboard and 0.709 on the private leaderboard. Comment: 3 pages, 1 figures, Instance-Level Recognition Workshop at ECCV 2022, Google Universal Image Embedding, 2nd place solution
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2210.08735 Zobrazit plný text záznamu View this record from Arxiv