4 Result(s)
within
Conference Paper
Lu Gong
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Chapter and Conference Paper
Credible Dual-X Modality Learning for Visible and Infrared Person Re-Identification
Visible-Infrared person Re-Identification (VI-ReID) is essential for public security. However, it poses a significant challenge due to the distinct reflection frequencies of visible and infrared modalities, le...
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Chapter and Conference Paper
Prototype-Augmented Contrastive Learning for Few-Shot Unsupervised Domain Adaptation
Unsupervised domain adaptation aims to learn a classification model from the source domain with much-supervised information, which is applied to the utterly unsupervised target domain. However, collecting enou...
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Chapter and Conference Paper
Learning Category Discriminability for Active Domain Adaptation
Active Domain Adaptation (ADA) attempts to improve the adaptation performance on a target domain by annotating informative target data with a limited budget. Previous ADA methods have significantly advanced by...
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Chapter and Conference Paper
Style Augmentation and Domain-Aware Parametric Contrastive Learning for Domain Generalization
The distribution shift between training data and test data degrades the performance of deep neural networks (DNNs), and domain generalization (DG) alleviates this problem by extracting domain-invariant feature...
