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3rd Place Solution to Google Landmark Recognition Competition 2021 (2110.02794v2)
Published 6 Oct 2021 in cs.CV
Abstract: In this paper, we show our solution to the Google Landmark Recognition 2021 Competition. Firstly, embeddings of images are extracted via various architectures (i.e. CNN-, Transformer- and hybrid-based), which are optimized by ArcFace loss. Then we apply an efficient pipeline to re-rank predictions by adjusting the retrieval score with classification logits and non-landmark distractors. Finally, the ensembled model scores 0.489 on the private leaderboard, achieving the 3rd place in the 2021 edition of the Google Landmark Recognition Competition.
- Cheng Xu (75 papers)
- Weimin Wang (52 papers)
- Shuai Liu (215 papers)
- Yong Wang (498 papers)
- Yuxiang Tang (1 paper)
- Tianling Bian (1 paper)
- Yanyu Yan (1 paper)
- Qi She (37 papers)
- Cheng Yang (168 papers)