6 citations · 6 across the 1 of their papers we have counts for
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Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation
Ye Huang, Di Kang, Wenjing Jia +2
Spatial and channel attentions, modelling the semantic interdependencies in spatial and channel dimensions respectively, have recently been widely used for semantic segmentation. H…
PDANet: Pyramid Density-aware Attention Net for Accurate Crowd Counting
Saeed Amirgholipour, Xiangjian He, Wenjing Jia +2
Crowd counting, i.e., estimating the number of people in a crowded area, has attracted much interest in the research community. Although many attempts have been reported, crowd cou…
See More Than Once -- Kernel-Sharing Atrous Convolution for Semantic Segmentation
Ye Huang, Qingqing Wang, Wenjing Jia +1
The state-of-the-art semantic segmentation solutions usually leverage different receptive fields via multiple parallel branches to handle objects with different sizes. However, emp…
DENet: A Universal Network for Counting Crowd with Varying Densities and Scales
Lei Liu, Jie Jiang, Wenjing Jia +3
Counting people or objects with significantly varying scales and densities has attracted much interest from the research community and yet it remains an open problem. In this paper…
FACLSTM: ConvLSTM with Focused Attention for Scene Text Recognition
Qingqing Wang, Wenjing Jia, Xiangjian He +3
Scene text recognition has recently been widely treated as a sequence-to-sequence prediction problem, where traditional fully-connected-LSTM (FC-LSTM) has played a critical role. D…
A-CCNN: adaptive ccnn for density estimation and crowd counting
Saeed Amirgholipour Kasmani, Xiangjian He, Wenjing Jia +2
Crowd counting, for estimating the number of people in a crowd using vision-based computer techniques, has attracted much interest in the research community. Although many attempts…