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

18 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV20201 cited

Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification

Wenao Ma, Shuang Yu, Kai Ma +3

Retinal artery/vein (A/V) classification plays a critical role in the clinical biomarker study of how various systemic and cardiovascular diseases affect the retinal vessels. Conve…

cs.CV20198 cited

A Real-time Global Inference Network for One-stage Referring Expression Comprehension

Yiyi Zhou, Rongrong Ji, Gen Luo +5

Referring Expression Comprehension (REC) is an emerging research spot in computer vision, which refers to detecting the target region in an image given an text description. Most ex…

cs.CV2019

Learning Rate Dropout

Huangxing Lin, Weihong Zeng, Xinghao Ding +3

The performance of a deep neural network is highly dependent on its training, and finding better local optimal solutions is the goal of many optimization algorithms. However, exist…

eess.IV20191 cited

Multi-sequence Cardiac MR Segmentation with Adversarial Domain Adaptation Network

Jiexiang Wang, Hongyu Huang, Chaoqi Chen +3

Automatic and accurate segmentation of the ventricles and myocardium from multi-sequence cardiac MRI (CMR) is crucial for the diagnosis and treatment management for patients suffer…

cs.CV201918 cited

Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes

Chengquan Zhang, Borong Liang, Zuming Huang +4

Previous scene text detection methods have progressed substantially over the past years. However, limited by the receptive field of CNNs and the simple representations like rectang…