2nd Place Solution to Google Landmark Retrieval 2021
Zhang Yuqi, Xu Xianzhe, Chen Weihua, Wang Yaohua, Zhang Fangyi, Wang, Fan, Li Hao
TL;DR
This paper details the 2nd place solution for the Google Landmark Retrieval 2021 challenge, utilizing innovative sampling and reranking strategies to improve image retrieval accuracy, achieving a 0.52995 mAP@100 score.
Contribution
It introduces continent-aware sampling and landmark-country reranking techniques, adapting person re-identification training tricks for landmark retrieval tasks.
Findings
Achieved 0.52995 mAP@100 on private leaderboard
Implemented continent-aware sampling strategy
Developed landmark-country aware reranking method
Abstract
This paper presents the 2nd place solution to the Google Landmark Retrieval 2021 Competition on Kaggle. The solution is based on a baseline with training tricks from person re-identification, a continent-aware sampling strategy is presented to select training images according to their country tags and a Landmark-Country aware reranking is proposed for the retrieval task. With these contributions, we achieve 0.52995 mAP@100 on private leaderboard. Code available at https://github.com/WesleyZhang1991/Google_Landmark_Retrieval_2021_2nd_Place_Solution
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Taxonomy
TopicsVideo Surveillance and Tracking Methods · Advanced Image and Video Retrieval Techniques · Human Pose and Action Recognition
MethodsAttentive Walk-Aggregating Graph Neural Network