Web: http://arxiv.org/abs/2209.08473

Sept. 20, 2022, 1:13 a.m. | Huanran Chen, Shitong Shao, Ziyi Wang, Zirui Shang, Jin Chen, Xiaofeng Ji, Xinxiao Wu

cs.CV updates on arXiv.org arxiv.org

Domain generalization aims to learn a model that can generalize well on the
unseen test dataset, i.e., out-of-distribution data, which has different
distribution from the training dataset. To address domain generalization in
computer vision, we introduce the loss landscape theory into this field.
Specifically, we bootstrap the generalization ability of the deep learning
model from the loss landscape perspective in four aspects, including backbone,
regularization, training paradigm, and learning rate. We verify the proposed
theory on the NICO++, PACS, and …

arxiv bootstrap landscape loss perspective

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