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Bias oriented unbiased data augmentation for cross-bias representation learning

文献类型：期刊论文

作者Li, Lei2,3; Tang, Fan2,3; Cao, Juan2,3; Li, Xirong1; Wang, Danding2,3
刊名MULTIMEDIA SYSTEMS
出版日期2022-10-25
页码14
关键词Cross-bias generalization Data augmentation Unbiased representation
ISSN号0942-4962
DOI10.1007/s00530-022-01013-6
英文摘要The biased cues in the training data may build strong connections between specific targets and unexpected concepts, leading the learned representations could not be applied to real-world data that does not contain the same biased cues. To learn cross-bias representations which can generalize on unbiased datasets by only using biased data, researchers focus on reducing the influence of biased cues through unbiased sampling or augmentation on the basis of artificial experience. However, the distributions of biased cues in the dataset are neglected, which limits the performance of these methods. In this paper, we propose a bias oriented data augmentation to enhance the cross-bias generalization by enlarging "safety" and "unbiasedness" constraints in the training data without manual prior intervention. The safety constraint is proposed to maintain the class-specific information for augmentation while the unbiasedness constraint reduces the statistical correlation of bias information and class labels. Experiments under different biased proportions on four synthetic/real-world datasets show that the proposed approach could improve the performance of other SOTA debiasing approaches (colored MNIST: 0.35-26.14%, corrupted CIFAR10: 3.14-8.44%, BFFHQ: 1.50% and BAR: 1.72%).
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000871828500001
出版者SPRINGER
源URL[http://119.78.100.204/handle/2XEOYT63/19770]  
专题中国科学院计算技术研究所期刊论文
通讯作者Tang, Fan
作者单位1.Renmin Univ China, Beijing 100872, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Li, Lei,Tang, Fan,Cao, Juan,et al. Bias oriented unbiased data augmentation for cross-bias representation learning[J]. MULTIMEDIA SYSTEMS,2022:14.
APA Li, Lei,Tang, Fan,Cao, Juan,Li, Xirong,&Wang, Danding.(2022).Bias oriented unbiased data augmentation for cross-bias representation learning.MULTIMEDIA SYSTEMS,14.
MLA Li, Lei,et al."Bias oriented unbiased data augmentation for cross-bias representation learning".MULTIMEDIA SYSTEMS (2022):14.

入库方式： OAI收割

来源：计算技术研究所

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