48 citations · 111 across the 9 of their papers we have counts for
9 papers
Document Layout Analysis via Dynamic Residual Feature Fusion
Xingjiao Wu, Ziling Hu, Xiangcheng Du +2
The document layout analysis (DLA) aims to split the document image into different interest regions and understand the role of each region, which has wide application such as optic…
ECNU-SenseMaker at SemEval-2020 Task 4: Leveraging Heterogeneous Knowledge Resources for Commonsense Validation and Explanation
Qian Zhao, Siyu Tao, Jie Zhou +3
This paper describes our system for SemEval-2020 Task 4: Commonsense Validation and Explanation (Wang et al., 2020). We propose a novel Knowledge-enhanced Graph Attention Network (…
A Real-Time Deep Network for Crowd Counting
Xiaowen Shi, Xin Li, Caili Wu +3
Automatic analysis of highly crowded people has attracted extensive attention from computer vision research. Previous approaches for crowd counting have already achieved promising…
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…
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…
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…
Fast Video Crowd Counting with a Temporal Aware Network
Xingjiao Wu, Baohan Xu, Yingbin Zheng +3
Crowd counting aims to count the number of instantaneous people in a crowded space, and many promising solutions have been proposed for single image crowd counting. With the ubiqui…
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…
Precise Temporal Action Localization by Evolving Temporal Proposals
Haonan Qiu, Yingbin Zheng, Hao Ye +3
Locating actions in long untrimmed videos has been a challenging problem in video content analysis. The performances of existing action localization approaches remain unsatisfactor…