2nd Place Solution to Google Landmark Retrieval 2021
arXiv:2110.04294
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
arXiv commentKaggle Competition, ICCV workshop
References in corpus (6)
- When Does Label Smoothing Help?
- Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset
- 1st Place Solution to Google Landmark Retrieval 2020
- Supporting large-scale image recognition with out-of-domain samples
- Towards A Fairer Landmark Recognition Dataset
- 3rd Place Solution to "Google Landmark Retrieval 2020"