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PoliTO-IIT-CINI Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition. (arXiv:2209.04525v1 [cs.CV])
Sept. 13, 2022, 1:14 a.m. | Mirco Planamente, Gabriele Goletto, Gabriele Trivigno, Giuseppe Averta, Barbara Caputo
cs.CV updates on arXiv.org arxiv.org
In this report, we describe the technical details of our submission to the
EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action
Recognition. To tackle the domain-shift which exists under the UDA setting, we
first exploited a recent Domain Generalization (DG) technique, called Relative
Norm Alignment (RNA). Secondly, we extended this approach to work on unlabelled
target data, enabling a simpler adaptation of the model to the target
distribution in an unsupervised fashion. To this purpose, we included in our
framework …
More from arxiv.org / cs.CV updates on arXiv.org
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