25 citations · 111 across the 31 of their papers we have counts for
4 papers · 1 filter
SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks
Weigang Lu, Yibing Zhan, Binbin Lin +6
Graph Convolutional Networks (GCNs) suffer from performance degradation when models go deeper. However, earlier works only attributed the performance degeneration to over-smoothing…
SynFace: Face Recognition with Synthetic Data
Haibo Qiu, Baosheng Yu, Dihong Gong +3
With the recent success of deep neural networks, remarkable progress has been achieved on face recognition. However, collecting large-scale real-world training data for face recogn…
TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition
Wenyuan Xue, Baosheng Yu, Wen Wang +2
A table arranging data in rows and columns is a very effective data structure, which has been widely used in business and scientific research. Considering large-scale tabular data…
Affordance Transfer Learning for Human-Object Interaction Detection
Zhi Hou, Baosheng Yu, Yu Qiao +2
Reasoning the human-object interactions (HOI) is essential for deeper scene understanding, while object affordances (or functionalities) are of great importance for human to discov…