21 citations · 46 across the 7 of their papers we have counts for
7 papers
Federated Graph Semantic and Structural Learning
Wenke Huang, Guancheng Wan, Mang Ye +1
Federated graph learning collaboratively learns a global graph neural network with distributed graphs, where the non-independent and identically distributed property is one of the…
Rotation Invariant Transformer for Recognizing Object in UAVs
Shuoyi Chen, Mang Ye, Bo Du
Recognizing a target of interest from the UAVs is much more challenging than the existing object re-identification tasks across multiple city cameras. The images taken by the UAVs…
Enhancing Visually-Rich Document Understanding via Layout Structure Modeling
Qiwei Li, Zuchao Li, Xiantao Cai +2
In recent years, the use of multi-modal pre-trained Transformers has led to significant advancements in visually-rich document understanding. However, existing models have mainly f…
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
Mang Ye, Xiuwen Fang, Bo Du +2
Federated learning (FL) has drawn increasing attention owing to its potential use in large-scale industrial applications. Existing federated learning works mainly focus on model ho…
An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection
Ziye Chen, Kate Smith-Miles, Bo Du +2
Accurately detecting lane lines in 3D space is crucial for autonomous driving. Existing methods usually first transform image-view features into bird-eye-view (BEV) by aid of inver…
Symmetric Uncertainty-Aware Feature Transmission for Depth Super-Resolution
Wuxuan Shi, Mang Ye, Bo Du
Color-guided depth super-resolution (DSR) is an encouraging paradigm that enhances a low-resolution (LR) depth map guided by an extra high-resolution (HR) RGB image from the same s…
Visible-Infrared Person Re-Identification via Patch-Mixed Cross-Modality Learning
Zhihao Qian, Yutian Lin, Bo Du
Visible-infrared person re-identification (VI-ReID) aims to retrieve images of the same pedestrian from different modalities, where the challenges lie in the significant modality d…