CrossNorm and SelfNorm for Generalization under Distribution Shifts
2021 IEEE/CVF International Conference on Computer Vision (ICCV)(2021)
摘要
Traditional normalization techniques (e.g., Batch Normalization and Instance Normalization) generally and simplistically assume that training and test data follow the same distribution. As distribution shifts are inevitable in real-world applications, well-trained models with previous normalization methods can perform badly in new environments. Can we develop new normalization methods to improve g...
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关键词
Training,Bridges,Computer vision,Codes,Robustness,Task analysis
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