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20162022
most citedLook More Than Once: An Accurate Detector for Text of Arbitrary Shapes

18 citations · 63 across the 20 of their papers we have counts for

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28 papers · 1 filter

cs.CV2022

Hint-dynamic Knowledge Distillation

Yiyang Liu, Chenxin Li, Xiaotong Tu +2

Knowledge Distillation (KD) transfers the knowledge from a high-capacity teacher model to promote a smaller student model. Existing efforts guide the distillation by matching their…

cs.CV2021

Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation

Chenxin Li, Qi Qi, Xinghao Ding +3

Medical imaging datasets usually exhibit domain shift due to the variations of scanner vendors, imaging protocols, etc. This raises the concern about the generalization capacity of…

cs.CV20215 cited

I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors

Chaoqi Chen, Zebiao Zheng, Yue Huang +2

Recent works on two-stage cross-domain detection have widely explored the local feature patterns to achieve more accurate adaptation results. These methods heavily rely on the regi…

cs.CV2021

Consistent Posterior Distributions under Vessel-Mixing: A Regularization for Cross-Domain Retinal Artery/Vein Classification

Chenxin Li, Yunlong Zhang, Zhehan Liang +3

Retinal artery/vein (A/V) classification is a critical technique for diagnosing diabetes and cardiovascular diseases. Although deep learning based methods achieve impressive result…

cs.CV20213 cited

Twice Mixing: A Rank Learning based Quality Assessment Approach for Underwater Image Enhancement

Zhenqi Fu, Xueyang Fu, Yue Huang +1

To improve the quality of underwater images, various kinds of underwater image enhancement (UIE) operators have been proposed during the past few years. However, the lack of effect…

cs.CV20203 cited

Few-shot Medical Image Segmentation using a Global Correlation Network with Discriminative Embedding

Liyan Sun, Chenxin Li, Xinghao Ding +3

Despite deep convolutional neural networks achieved impressive progress in medical image computing and analysis, its paradigm of supervised learning demands a large number of annot…