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20152019
most citedEvaluating Two-Stream CNN for Video Classification

114 citations · 140 across the 4 of their papers we have counts for

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9 papers · 1 filter

cs.CV2019

Cascaded Detail-Preserving Networks for Super-Resolution of Document Images

Zhichao Fu, Yu Kong, Yingbin Zheng +4

The accuracy of OCR is usually affected by the quality of the input document image and different kinds of marred document images hamper the OCR results. Among these scenarios, the…

cs.CV2019

Scene Text Recognition with Temporal Convolutional Encoder

Xiangcheng Du, Tianlong Ma, Yingbin Zheng +3

Texts from scene images typically consist of several characters and exhibit a characteristic sequence structure. Existing methods capture the structure with the sequence-to-sequenc…

cs.CV2019

Edge-Aware Deep Image Deblurring

Zhichao Fu, Tianlong Ma, Yingbin Zheng +3

Image deblurring is a fundamental and challenging low-level vision problem. Previous vision research indicates that edge structure in natural scenes is one of the most important fa…

cs.CV2019

Detecting Curve Text with Local Segmentation Network and Curve Connection

Zhao Zhou, Hao Ye, Luhui Chen +1

Curve text or arbitrary shape text is very common in real-world scenarios. In this paper, we propose a novel framework with the local segmentation network (LSN) followed by the cur…

cs.CV2018

Adaptive Scenario Discovery for Crowd Counting

Xingjiao Wu, Yingbin Zheng, Hao Ye +3

Crowd counting, i.e., estimation number of the pedestrian in crowd images, is emerging as an important research problem with the public security applications. A key component for t…

cs.CV2018

Crowd Counting with Density Adaption Networks

Li Wang, Weiyuan Shao, Yao Lu +3

Crowd counting is one of the core tasks in various surveillance applications. A practical system involves estimating accurate head counts in dynamic scenarios under different light…