Rui She
19 Papers
Rui She is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 8 publications.
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Papers
PointDifformer: Robust Point Cloud Registration with Neural Diffusion and Transformer
Rui She,Qiyu Kang,Sijie Wang,Wee Peng Tay,Kai Zhao,Yang Song,Tianyu Geng,Yi Xu,Diego Navarro Navarro,Andreas Hartmannsgruber +9 more
TL;DR: This work proposes a robust point cloud registration approach that leverages graph neural partial differential equations (PDEs) and heat kernel signatures to extract high-dimensional features from point clouds by aggregating information from the 3-D point neighborhood, thereby enhancing the robustness of the feature representations.
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RobustMat: Neural Diffusion for Street Landmark Patch Matching under Challenging Environments.
Rui She,Qiyu Kang,Sijie Wang,Yuan-Rui Yang,Kai Zhao,Yang Song,Wee-Peng Tay +6 more
TL;DR: This work proposes an approach, named RobustMat, which derives its robustness to perturbations from neural differential equations, which is evaluated on several street scene datasets and demonstrated to achieve state-of-the-art matching results under environmental perturbation.
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Image Patch-Matching With Graph-Based Learning in Street Scenes
Rui She,Qiyu Kang,Sijie Wang,Wee-Peng Tay,Yong Liang Guan,Diego Navarro Navarro,Andreas Hartmannsgruber +6 more
TL;DR: In this paper , a joint feature and metric learning model with graph-based learning is proposed to match landmark patches from a real-time image captured by an on-vehicle camera with landmark patches in an image database.
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DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition
Sijie Wang,Rui She,Qiyu Kang,Xingchao Jian,Kai Zhao,Yang Song,Wee Peng Tay +6 more
TL;DR: This work presents DistilVPR, a novel distillation pipeline for VPR that enhances the diversity of feature relationships, including Euclidean, spherical, and hyperbolic relationship modules, thereby enhancing the overall representational capacity.
Location Learning for AVs: LiDAR and Image Landmarks Fusion Localization with Graph Neural Networks
Qiyu Kang,Rui She,Sijie Wang,Wee-Peng Tay,Diego Navarro Navarro,Andreas Hartmannsgruber +5 more
- 08 Oct 2022
TL;DR: Li et al. as discussed by the authors used a CNN to extract features from RGB images captured by an on-vehicle camera and a Graph Neural Network (GNN) to integrate measurements from LiDAR scans.
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