48 citations · 74 across the 6 of their papers we have counts for
6 papers
Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis
Luwei Xiao, Xingjiao Wu, Wen Wu +2
Nowadays, with the explosive growth of multimodal reviews on social media platforms, multimodal sentiment analysis has recently gained popularity because of its high relevance to t…
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…
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…
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…