简介,团队介绍

Our research interest includes machine learning,Riemannian manifold and computer vision. We have published more than 20 papers at the top international AI conferences with total google scholar citations 100+

👥 Team Members

  • Co-founders: Rui Wang,Ziheng Chen
  • Members@2023: Chen Hu,Shaocheng Jin, Zihao Bi
  • Members@2024: Join us!

🔥 News

  • 2024.04:  🎉🎉 One paper on Riemannian Residual Learning Mechanism on SPD manifolds was accepted to IJCNN 2024.
  • 2024.04:  🎉🎉 One paper on Grassmannian self-attention was accepted to IJCAI 2024. Congrats Rui and Chen!
  • 2024.03:  🎉🎉 Our CVPR 2024 paper on Riemannian classifiers was selected as poster to VALSE 2024.
  • 2024.03:  🎉🎉 One paper on SPD deep metric learning was early accessed in TNNLS.
  • 2024.02:  🎉🎉 One paper on Riemannian classifiers on SPD manifolds was accepted to CVPR 2024.
  • 2024.01:  🎉🎉 One paper on Riemannian batch normalization on general Lie groups was accepted to ICLR 2024.

📝 Seleted Publications

IJCAI 2024
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A Grassmannian Manifold Self-Attention Network for Signal Classification

Rui Wang, Chen Hu, Ziheng Chen†, Xiao-Jun Wu†, Xiaoning Song

TNNLS 2024
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SPD Manifold Deep Metric Learning for Image Set Classification

Rui Wang, Xiao-Jun Wu†, Ziheng Chen, Cong Hu, Josef Kittler

TCSVT 2024
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Deep Metric Learning on the SPD Manifold for Image Set Classification

Rui Wang, Xiao-Jun Wu†, Tianyang Xu, Cong Hu, Josef Kittler

  • ICLR 2024Ziheng Chen, Yue Song, Yunmei Liu, Nicu Sebe, A Lie Group Approach to Riemannian Batch Normalization. [PDF] [Code] [Slides] [Poster] [Video]

  • CVPR 2024Ziheng Chen, Yue Song, Gaowen Liu, Ramana Rao Kompella, Xiaojun Wu, Nicu Sebe, Riemannian Multinomial Logistics Regression for SPD Neural Networks. [PDF] [Code] [Slides] [Poster] [Video]

  • AAAI 2023Ziheng Chen, Tianyang Xu, Xiao-Jun Wu†, Rui Wang, Zhiwu Huang, Josef Kittler, Riemannian Local Mechanism for SPD Neural Networks. [PDF] [Code] [Slides] [Poster]

  • Neural networks 2023Rui Wang, Xiao-Jun Wu†, Tianyang Xu, Cong Hu, Josef Kittler, U-SPDNet: An SPD manifold learning-based neural network for visual classification. [PDF]

  • Neural networks 2022Rui Wang, Xiao-Jun Wu†, Ziheng Chen, Tianyang Xu, Josef Kittler, Learning a discriminative SPD manifold neural network for image set classification. [PDF]

  • IEEE TBD 2021Ziheng Chen, Tianyang Xu, Xiao-Jun Wu†, Rui Wang, Josef Kittler, Hybrid Riemannian Graph-Embedding Metric Learning for Image Set Classification. [PDF] [Code]

  • IEEE TBD 2020Rui Wang, Xiao-Jun Wu†, Kai-Xuan Chen, Josef Kittler, Multiple Riemannian Manifold-Valued Descriptors Based Image Set Classification With Multi-Kernel Metric Learning. [PDF]

✨ Scientific research projects

  1. National Natural Science Foundation of China (NSFC), research on lightweight Riemannian neural networks, 2024.01-2026.12 (hosted)
  2. Natural Science Foundation of Jiangsu Province, research on Riemannian deep learning technique for open scene object recognition, 2023.09-2026.08 (hosted)
  3. Fundamental Research Funds for the Central Universities, research on Riemannian deep learning technique for complicated visual classification, 2024.01-2025.12 (hosted)
  4. National Natural Science Foundation of China (NSFC), research on neural representation and modeling for dynamic scene, 2024.01-2026.12 (key member)
  5. National Key Research and Development Program of China, research on AI-based food safety tracking and supervision, 2024.01-2028.12 (key member)
  6. Key Project of Wuxi Municipal Health Commission, research on AI-based ECG analysis and prediction, 2024.01-2025.12 (key member)

🎖 Honors and Awards

  • 2024.05, Our team won the first prize in the Eastern Regional Competition of the 15th China College Student Service Outsourcing Innovation and Entrepreneurship Competition.

📖 Courses

To obtain basic foundations for my research, I have self-studied several math courses, most of which were done during my master studies:

  • Mathematical Analysis I, II, III, Real Analysis, Complex Analysis, Functional Analysis;
  • Advanced Algebra I, II, Abstract Algebra I;
  • Topology, Differential Geometry, Differential Manifolds, Riemannian Geometry;
  • Differential Equations, Convex Optimization, Numerical Optimization…