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pro vyhledávání: '"Long, Shaocong"'
Autor:
Long, Shaocong, Zhou, Qianyu, Li, Xiangtai, Lu, Xuequan, Ying, Chenhao, Luo, Yuan, Ma, Lizhuang, Yan, Shuicheng
Domain generalization~(DG) aims at solving distribution shift problems in various scenes. Existing approaches are based on Convolution Neural Networks (CNNs) or Vision Transformers (ViTs), which suffer from limited receptive fields or quadratic compl
Externí odkaz:
http://arxiv.org/abs/2404.07794
Domain generalization(DG) endeavors to develop robust models that possess strong generalizability while preserving excellent discriminability. Nonetheless, pivotal DG techniques tend to improve the feature generalizability by learning domain-invarian
Externí odkaz:
http://arxiv.org/abs/2309.16483
Generalization under the distribution shift has been a great challenge in computer vision. The prevailing practice of directly employing the one-hot labels as the training targets in domain generalization~(DG) can lead to gradient conflicts, making i
Externí odkaz:
http://arxiv.org/abs/2309.16460