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20162022
most citedRevisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning

43 citations · 88 across the 13 of their papers we have counts for

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Showing 2020Show all

10 papers · 1 filter

cs.CV2020★ 1 cited

CariMe: Unpaired Caricature Generation with Multiple Exaggerations

Zheng Gu, Chuanqi Dong, Jing Huo +2

Caricature generation aims to translate real photos into caricatures with artistic styles and shape exaggerations while maintaining the identity of the subject. Different from the…

cs.LG2020

Learning-based Computer-aided Prescription Model for Parkinson's Disease: A Data-driven Perspective

Yinghuan Shi, Wanqi Yang, Kim-Han Thung +5

In this paper, we study a novel problem: "automatic prescription recommendation for PD patients." To realize this goal, we first build a dataset by collecting 1) symptoms of PD pat…

cs.CV2020★ 2 cited

Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition

Wen Ji, Kelei He, Jing Huo +2

Caricature attributes provide distinctive facial features to help research in Psychology and Neuroscience. However, unlike the facial photo attribute datasets that have a quantity…

cs.CV2020

Manifold Alignment for Semantically Aligned Style Transfer

Jing Huo, Shiyin Jin, Wenbin Li +4

Most existing style transfer methods follow the assumption that styles can be represented with global statistics (e.g., Gram matrices or covariance matrices), and thus address the…

eess.IV2020

Crossover-Net: Leveraging the Vertical-Horizontal Crossover Relation for Robust Segmentation

Qian Yu, Yinghuan Shi, Yefeng Zheng +3

Robust segmentation for non-elongated tissues in medical images is hard to realize due to the large variation of the shape, size, and appearance of these tissues in different patie…

cs.CV2020

Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation

Tiexin Qin, Wenbin Li, Yinghuan Shi +1

Few-shot learning aims to learn a new concept when only a few training examples are available, which has been extensively explored in recent years. However, most of the current wor…