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Google Landmark Retrieval 2021 Competition Third Place Solution

2021-10-09 · Qishen Ha, Bo Liu, Hongwei Zhang

We present our solutions to the Google Landmark Challenges 2021, for both the retrieval and the recognition tracks. Both solutions are ensembles of transformers and ConvNet models based on Sub-center ArcFace with dynamic margins. Since the two tracks share the same training data, we used the same pipeline and training approach, but with different model selections for the ensemble and different post-processing. The key improvement over last year is newer state-of-the-art vision architectures, especially transformers which significantly outperform ConvNets for the retrieval task. We finished third and fourth places for the retrieval and recognition tracks respectively.

📄 PDF Abstract BibTeX arXiv:2110.04619

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Retrieval

Methods 이 논문이 사용한 방법론

ArcFace ArcFace, or Additive Angular Margin Loss, is a loss function used in face recognition tasks. The softmax is traditionally used…

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