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Bag of Tricks for Out-of-Distribution Generalization. (arXiv:2208.10722v1 [cs.CV])
Aug. 24, 2022, 1:14 a.m. | Zining Chen, Weiqiu Wang, Zhicheng Zhao, Aidong Men, Hong Chen
cs.CV updates on arXiv.org arxiv.org
Recently, out-of-distribution (OOD) generalization has attracted attention to
the robustness and generalization ability of deep learning based models, and
accordingly, many strategies have been made to address different aspects
related to this issue. However, most existing algorithms for OOD generalization
are complicated and specifically designed for certain dataset. To alleviate
this problem, nicochallenge-2022 provides NICO++, a large-scale dataset with
diverse context information. In this paper, based on systematic analysis of
different schemes on NICO++ dataset, we propose a simple but …
More from arxiv.org / cs.CV updates on arXiv.org
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