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Guangzhen Liu

2 accepted papers

2021

Contrastive prototype learning with augmented embeddings for few-shot learning

UAI 2021poster

Most recent few-shot learning (FSL) methods are based on meta-learning with episodic training. In each meta-training episode, a discriminative feature embedding and/or classifier are first constructed from a support set in an inner loop, and then evaluated in an outer loop using a query set for mode…

Cited by 43SourcePDFScholar
2021

L2M-GAN: Learning To Manipulate Latent Space Semantics for Facial Attribute Editing

CVPR 2021poster

A deep facial attribute editing model strives to meet two requirements: (1) attribute correctness -- the target attribute should correctly appear on the edited face image; (2) irrelevance preservation -- any irrelevant information (e.g., identity) should not be changed after editing. Meeting both re…

Cited by 86PDFcodeScholar