3 citations · 3 across the 4 of their papers we have counts for
3 papers
Geometry-Guided Self-Supervision for Ultra-Fine-Grained Recognition with Limited Data
Shijie Wang, Yadan Luo, Zijian Wang +3
This paper investigates the intrinsic geometrical features of highly similar objects and introduces a general self-supervised framework called the Geometric Attribute Exploration N…
Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters
Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu +2
Overfitting to the source domain is a common issue in gradient-based training of deep neural networks. To compensate for the over-parameterized models, numerous regularization tech…
Multi-component Image Translation for Deep Domain Generalization
Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh +1
Domain adaption (DA) and domain generalization (DG) are two closely related methods which are both concerned with the task of assigning labels to an unlabeled data set. The only di…