Rui Shao (邵睿)  

Professor, HIT (Shenzhen)



School of Computer Science and Technology,

Harbin Institute of Technology (Shenzhen)

Email: shaorui[AT]hit.edu.cn, rshaojimmy[AT]gmail.com

[Google Scholar] [GitHub] [LinkedIn] [CV] [中文简历] [中文主页]


News

  • 11/2023: We have released the arXiv paper for our Multi-Modal Large Language Model (MLLM)- JiuTian-LION . Enjoy it!
  • 08/2023: We have built the GitHub Repo for our Multi-Modal Large Language Model (MLLM)- JiuTian . Enjoy it!
  • 04/2023: I have released the code and dataset of our CVPR 2023 work in our GitHub Repo . Enjoy it!
  • 02/2023: I have one paper accepted by CVPR 2023. Code and dataset will be released soon. Please stay tuned!
  • 07/2022: I have one paper accepted by ECCV 2022. We have released the code and dataset in our project page
  • 05/2022: I have released the code of Federated Generalized Face Presentation Attack Detection in TNNLS 2022. Codes
  • 04/2022: I have one paper accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS) .
  • 03/2022: I have released the code of Open-set Adversarial Defense with Clean-Adversarial Mutual Learning in IJCV 2022. Codes
  • 01/2022: The extension of our ECCV 2020 paper has been accepted by International Journal of Computer Vision (IJCV).
  • 08/2020: I have released the code of Open-set Adversarial Defense in ECCV 2020. Codes
  • 07/2020: I have one paper accepted by ECCV 2020. See you online!
  • 11/2019: I have released the code of Regularized Fine-grained Meta Face Anti-spoofing in AAAI 2020. Codes
  • 11/2019: I have one paper accepted by AAAI 2020. See you at New York City, USA!
  • 10/2019: I have one paper one paper accepted by IET Image Processing.
  • 07/2019: I have released the code of Multi-adversarial Discriminative Deep Domain Generalization for FAS in CVPR 2019. Codes
  • 07/2019: I have released the code of Joint Discriminative Learning of Deep Dynamic Textures for 3D Mask FAS in TIFS 2019. Codes
  • 02/2019: I have one paper accepted by CVPR 2019. See you at Long Beach, USA!
  • 02/2019: One paper is accepted by IEEE Transactions on Industrial Electronics.
  • 08/2018: I have one paper accepted by IEEE Transactions on Information Forensics and Security .
  • 07/2018: I have released the code of Hierarchical Adversarial Deep Domain Adaptation in ACMMM 2018. Codes
  • 07/2018: I have one paper accepted by ACM MM 2018. See you at Seoul, Korea!
  • 08/2018: I have a new homepage.

About Me

I am currently a Professor at School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen). Prior to that, I was a postdoc at Nanyang Technological University, Singapore, working with Prof. Ziwei Liu and Prof. Chen Change Loy.

I received my PhD degree from Department of Computer Science, Hong Kong Baptist University in 2021, supervised by Prof. Pong C. Yuen, and my bachelor degree from School of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC) in 2015. I also spent a memorable high-school time in Shenzhen Foreign Languages School. I visited the Johns Hopkins University for 6 months in 2020.

My current research focuses on Multi-Modal Large Language Model (MLLM)- JiuTian , multi-modal learning (e.g., vision-language pre-training and content generation) and its trustworthy issues.

Biography

  • 2021-2023, Research Fellow, MMLab@NTU, Singapore
  • 2021.7- 2021.11, Researcher, SenseTime, Shenzhen, China, participating project of MMhuman3D codebase.
  • 2017-2021, Ph.D., Department of Computer Science, Hong Kong Baptist University, Hong Kong, China
  • 2020.2-2020.7, Visiting scholar at Johns Hopkins University, working with Prof. Vishal M Patel, Baltimore, U.S.
  • 2011-2015, B.S., School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Pre-prints

    LION : Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge

    Gongwei Chen, Leyang Shen, Rui Shao†, Xiang Deng, Liqiang Nie†

    [arXiv] [Code] [Project Page]

    Detecting and Grounding Multi-Modal Media Manipulation and Beyond

    Rui Shao, Tianxing Wu, Jianlong Wu, Liqiang Nie, Ziwei Liu

    [arXiv] [Code]

    DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection

    Rui Shao, Tianxing Wu, Liqiang Nie, Ziwei Liu

    [arXiv] [Code]

    Robust Sequential DeepFake Detection

    Rui Shao, Tianxing Wu, Ziwei Liu

    [arXiv] [Code]

    Publications

    Detecting and Grounding Multi-Modal Media Manipulation

    Rui Shao, Tianxing Wu, Ziwei Liu

    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

    [arXiv] [Code] [Project Page] [Press]

    Video Infilling with Rich Motion Prior

    Xinyu Hou, Liming Jiang, Rui Shao, Chen Change Loy

    British Machine Vision Conference (BMVC), 2023.

    [arXiv] [Code]

    Detecting and Recovering Sequential DeepFake Manipulation

    Rui Shao, Tianxing Wu, Ziwei Liu

    European Conference on Computer Vision (ECCV), 2022.

    [arXiv] [Code] [Project Page] [Poster] [Press1] [Press2] [Press3] [Press4]

    Open-set Adversarial Defense with Clean-Adversarial Mutual Learning

    Rui Shao, Pramuditha Perera, Pong C. Yuen, Vishal M. Patel

    International Journal of Computer Vision (IJCV), 2022

    [arXiv] [PDF] [Code]

    Federated Generalized Face Presentation Attack Detection

    Rui Shao, Pramuditha Perera, Pong C. Yuen, Vishal M. Patel

    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

    [arXiv] [PDF] [Code]

    Federated Test-Time Adaptive Face Presentation Attack Detection with Dual-Phase Privacy Preservation

    Rui Shao, Bochao Zhang, Pong C. Yuen, Vishal M. Patel

    IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2021

    [arXiv] [PDF]

    Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification

    Chong Yin, Siqi Liu, Rui Shao, Pong C. Yuen,

    Medical Image Computing and Computer Assisted Interventions (MICCAI), 2021

    [PDF]

    Open-set Adversarial Defense

    Rui Shao, Pramuditha Perera, Pong C. Yuen, Vishal M. Patel

    European Conference on Computer Vision (ECCV), 2020

    [arXiv] [PDF] [Code]

    Regularized Fine-grained Meta Face Anti-spoofing

    Rui Shao, Xiangyuan Lan, Pong C. Yuen

    Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020

    [arXiv] [PDF] [Poster] [Code]

    Multi-adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection

    Rui Shao, Xiangyuan Lan, Jiawei Li, Pong C. Yuen

    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019

    [PDF] [Poster] [Code] [Model]

    Joint Discriminative Learning of Deep Dynamic Textures for 3D Mask Face Anti-spoofing

    Rui Shao, Xiangyuan Lan, Pong C. Yuen

    IEEE Transactions on Information Forensics and Security (TIFS), 2019

    [PDF] [Code]

    Adversarial Auto-encoder for Unsupervised Deep Domain Adaptation

    Rui Shao, Xiangyuan Lan

    IET Image Processing. (IET-IPR), 2019

    [PDF]

    Feature Constrained by Pixel: Hierarchical Adversarial Deep Domain Adaptation

    Rui Shao, Xiangyuan Lan, Pong C. Yuen

    ACM international conference on Multimedia (ACM MM), 2018

    [PDF] [Poster] [Code]


    Deep Convolutional Dynamic Texture Learning with Adaptive Channel-discriminability for 3D Mask Face Anti-spoofing

    Rui Shao, Xiangyuan Lan, Pong C. Yuen

    International Joint Conference on Biometrics (IJCB), 2017

    [PDF]


    Learning Modality-Consistency Feature Templates: A Robust RGB-Infrared Tracking System

    Xiangyuan Lan, Mang Ye, Rui Shao, Bineng Zhong, Pong C. Yuen, Huiyu Zhou

    IEEE Transactions on Industrial Electronics (TIE), 2019

    [PDF]

    Awards

  • 2018/19 Computer Science Department RPg Performance Award
  • 2017/18 Computer Science Department RPg Performance Award

  • Services

    Invited Reviewer for:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Information Forensics and Security, Neural Networks, Pattern Recognition, Journal of Selected Topics in Signal Processing, Journal of Electronic Imaging
  • CVPR, ICCV, ECCV, NeurIPS, AAAI, IJCAI, ACM MM, ICPR, ICB
  • Program Committee Member for: AAAI 2021 2022

  • Collaborators

  • Prof. Vishal M Patel, Johns Hopkins University
  • Dr. Xiangyuan Lan, Peng Cheng Laboratory
  • Dr. Pramuditha Perera, Johns Hopkins University, AWS AI Lab
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