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      Meet-in-the-middle: Multi-scale upsampling and matching \\ for cross-resolution face recognition

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          Abstract

          In this paper, we aim to address the large domain gap between high-resolution face images, e.g., from professional portrait photography, and low-quality surveillance images, e.g., from security cameras. Establishing an identity match between disparate sources like this is a classical surveillance face identification scenario, which continues to be a challenging problem for modern face recognition techniques. To that end, we propose a method that combines face super-resolution, resolution matching, and multi-scale template accumulation to reliably recognize faces from long-range surveillance footage, including from low quality sources. The proposed approach does not require training or fine-tuning on the target dataset of real surveillance images. Extensive experiments show that our proposed method is able to outperform even existing methods fine-tuned to the SCFace dataset.

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          Author and article information

          Journal
          28 November 2022
          Article
          2211.15225
          02ca18bd-52f1-4237-8ea8-afb4661a42ed

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          cs.CV

          Computer vision & Pattern recognition
          Computer vision & Pattern recognition

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