3rd Place Solution to Google Landmark Recognition Competition 2021
Cheng Su Xu, Weimin Wang, Shuai Liu, Yong Wang, Yuxiang Tang, Tianling Bian, Yanyu Yan, Qi She, Cheng Hong Yang · arXiv (Cornell University) · 2021
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.