activity
20132023
most citedFACLSTM: ConvLSTM with Focused Attention for Scene Text Recognition

25 citations · 64 across the 12 of their papers we have counts for

collaborators

13 papers

cs.CV2023

Point Clouds Are Specialized Images: A Knowledge Transfer Approach for 3D Understanding

Jiachen Kang, Wenjing Jia, Xiangjian He +1

Self-supervised representation learning (SSRL) has gained increasing attention in point cloud understanding, in addressing the challenges posed by 3D data scarcity and high annotat…

cs.CV2023

CARD: Semantic Segmentation with Efficient Class-Aware Regularized Decoder

Ye Huang, Di Kang, Liang Chen +5

Semantic segmentation has recently achieved notable advances by exploiting "class-level" contextual information during learning. However, these approaches simply concatenate class-…

cs.CV2022★ 4 cited

Leveraging Systematic Knowledge of 2D Transformations

Jiachen Kang, Wenjing Jia, Xiangjian He

The existing deep learning models suffer from out-of-distribution (o.o.d.) performance drop in computer vision tasks. In comparison, humans have a remarkable ability to interpret i…

cs.CV2022

CAR: Class-aware Regularizations for Semantic Segmentation

Ye Huang, Di Kang, Liang Chen +4

Recent segmentation methods, such as OCR and CPNet, utilizing "class level" information in addition to pixel features, have achieved notable success for boosting the accuracy of ex…

cs.MM2021

What's Wrong with the Bottom-up Methods in Arbitrary-shape Scene Text Detection

Chengpei Xu, Wenjing Jia, Tingcheng Cui +3

The latest trend in the bottom-up perspective for arbitrary-shape scene text detection is to reason the links between text segments using Graph Convolutional Network (GCN). Notwith…

cs.CV2021★ 3 cited

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…