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Open accessProceedings ArticleDOI
Kresimir Delac, Mislav Grgic, Sonja Grgic 
27 Jun 2007
7 Citations
Our experimental results indicate that face recognition performance in JPEG2000 compressed domain is comparable, or even better in some cases, than face recognition performance in pixel domain.
In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions.
In this paper, we present an effective and unsupervised face Re-ID system which simultaneously re-identifies multiple faces for HRI.
Such an approach confuses the state-of-the-art public Face ID model LResNet100E-IR, ArcFace@ms1m-refine-v2 and is transferable to other Face ID models.
In addition, we show that face-space super-resolution is more robust to registration errors and noise than pixel-domain super-resolution because of the addition of model-based constraints.
Extensive experiments on the challenging faces data sets EUROCOM and CurtinFaces for face verification as well as the BIWI RGBD-ID data set for person re-identification demonstrate the effectiveness of our proposed approach.

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