Rui Shao (邵睿)

Professor

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

10/2024: We have built GitHub Orgnization of JiuTian-VL that will post all information about our JiuTian MLLM.
10/2024: I have one paper about the adapter of large vision models accepted by International Journal of Computer Vision (IJCV). Cheers!
10/2024: Two papers about MLLMs are accepted at NeurIPS 2024, including contributions from a 2nd-year undergraduate. Cheers!
07/2024: One paper about Audio-Visual Multimodal Large Language Model accepted by ECCV 2024.
02/2024: Our Multimodal Large Language Model (MLLM)- JiuTian-LION has been accepted by CVPR 2024. Cheers!
02/2024: The extension of our CVPR 2023 paper has been accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Cheers!
11/2023: We have released the arXiv paper for our Multimodal Large Language Model (MLLM)- JiuTian-LION . Enjoy it!
08/2023: We have built the GitHub Repo for our Multimodal 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.

I am interested in computer vision and multimodal learning. My current research focuses on Multimodal Large Language Model (MLLM) (e.g., "JiuTian" MLLM ) and its trustworthy issues.

Looking for self-motivated Ph.D/M.S./Undergraduate students. [2024硕士/博士招生, 4-5名硕士, 2名博士]
Looking for PostDocs in computer vision and MLLM.

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 (* denotes corresponding authors)

	Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thought Zaijing Li, Rui Shao*, Gongwei Chen, Dongmei Jiang, Liqiang Nie [arXiv]

	Token-level Correlation-guided Compression for Efficient Multimodal Document Understanding Renshan Zhang, Yibo Lyu, Rui Shao, Gongwei Chen, Weili Guan, Liqiang Nie [arXiv]

	Robust Sequential DeepFake Detection Rui Shao, Tianxing Wu, Ziwei Liu [arXiv] [Code]

Selected Publications (* denotes corresponding authors)

	Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks Zaijing Li, Yuquan Xie, Rui Shao, Gongwei Chen, Dongmei Jiang, Liqiang Nie Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. [arXiv] [Code] [Project Page]

	MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models Leyang Shen, Gongwei Chen, Rui Shao, Weili Guan, Liqiang Nie Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. [arXiv] [Code]

	LION: Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge Gongwei Chen, Leyang Shen, Rui Shao, Xiang Deng, Liqiang Nie IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [arXiv] [Code] [Project Page] [Press]

	DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection Rui Shao, Tianxing Wu, Liqiang Nie, Ziwei Liu International Journal of Computer Vision (IJCV), 2024 [arXiv] [Code]

	Detecting and Grounding Multi-Modal Media Manipulation and Beyond Rui Shao, Tianxing Wu, Jianlong Wu, Liqiang Nie, Ziwei Liu IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024 [arXiv] [Code] [Project Page] [Press]

	CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios Qilang Ye, Zitong Yu, Rui Shao, Xinyu Xie, Philip Torr, Xiaochun Cao European Conference on Computer Vision (ECCV), 2024. [arXiv] [Code] [Project Page]

	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]