Shuangrui Ding

Shuangrui Ding (丁双睿)

I am a first-year Ph.D. student in the Multi-Media Lab at The Chinese University of Hong Kong, supervised by Prof. Dahua Lin. My current research interest spans the multi-modality large language model and video understanding.

I obtained my Master's degree in Electrical Engineering from Shanghai Jiao Tong University in 2023, where I was advised by Prof. Hongkai Xiong. Prior to that, I earned a Bachelor's degree in Computer Science from the University of Michigan, along with a dual degree in Electrical and Computer Engineering from Shanghai Jiao Tong University in 2021.

Please drop me an email if you are interested in collaboration with me.

Email / CV / Google Scholar / Github

News

[Jul. 2023] Two papers have been accepted at ICCV 2023. One focuses on video Transformer pruning, and the other on self-supervised video object discovery.

Preprint

InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition
Pan Zhang*, Xiaoyi Dong*, Bin Wang, Yuhang Cao, Chao Xu, Linke Ouyang, Zhiyuan Zhao, Shuangrui Ding, Songyang Zhang, Haodong Duan, Wenwei Zhang, Hang Yan, Xinyue Zhang, Wei Li, Jingwen Li, Kai Chen, Conghui He, Xingcheng Zhang, Yu Qiao, Dahua Lin, Jiaqi Wang
preprint, 2023
arXiv / code

A vision-language large model that enables advanced image-text comprehension and composition.

Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object Segmentation
Shuangrui Ding*, Rui Qian*, Haohang Xu, Dahua Lin, Hongkai Xiong
preprint, 2023
arXiv / code

Learn robust spatio-temporal corrependence on top of DINO-pretrained Transformer without any annotation.

Publications(* equal contribution)

	Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation Shuangrui Ding, Peisen Zhao, Xiaopeng Zhang, Rui Qian, Hongkai Xiong, Qi Tian ICCV, 2023 Project page / arXiv / pdf / code / poster / slides Propose token pruning strategy for video Transformers to offer a competitive speed-accuracy trade-off without additional training or parameters.
	Semantics Meets Temporal Correspondence: Self-supervised Object-centric Learning in Videos Rui Qian, Shuangrui Ding, Xian Liu, Dahua Lin ICCV, 2023 arXiv / pdf / code / poster Jointly utilizes high-level semantics and low-level temporal correspondence for object-centric learning in videos without any supervision.
	Static and Dynamic Concepts for Self-supervised Video Representation Learning Rui Qian, Shuangrui Ding, Xian Liu, Dahua Lin ECCV, 2022 arXiv / code / slide Learn static and dynamic visual concepts in videos to aggregate local patterns with similar semantics to boost unsupervised video representation.
	Dual Contrastive Learning for Spatio-temporal Representation Shuangrui Ding, Rui Qian, Hongkai Xiong ACM MM, 2022 arXiv / poster / video / code Present a novel dual contrastive formulation to decouple the static/dynamic features and thus mitigate the background bias.
	Motion-aware Contrastive Video Representation Learning via Foreground-background Merging Shuangrui Ding, Maomao Li, Tianyu Yang, Rui Qian, Haohang Xu, Qingyi Chen, Jue Wang, Hongkai Xiong CVPR, 2022 Project page / arXiv / code / Chinese coverage / poster Mitigate the background bias in self-supervised video representation learning via copy-pasting the foreground onto the other backgrounds.
	Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization Rui Qian, Yuxi Li, Huabin Liu, John See, Shuangrui Ding, Xian Liu, Dian Li, Weiyao Lin ICCV, 2021 arXiv / code Self-supervised video representation learning from the perspective of both high-level semantics and lower-level characteristics
	Towards More Practical Adversarial Attacks on Graph Neural Networks Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei NeurIPS, 2020 arXiv / slides / video / code Exploiting the structural inductive biases of GNNs, the restricted black-box adversarial attacks can be conducted effectively.

Awards

CUHK Vice-Chancellor's Ph.D. Scholarship (80,000 HKD), Graduate school of CUHK. 2023

Graduate National Scholarship (Top 2%), Ministry of Education of China. 2022

Shanghai Excellent Graduate (Top 5%), Shanghai Municipal Education Commission. 2021

Finalist winner (Top 0.3%), Mathematical Contest in Modeling. 2019

National Scholarship (Top 2%), Ministry of Education of China. 2018

Professional Services

Reviewer: ECCV'22, AAAI'23-24, ICLR'23-24, CVPR'23, ICCV'23, ACM MM'23, NeruIPS'23.

Misc

1. My favorite sports is soccer. I was the captain of UM-SJTU JI soccer team during season 2018. Besides, I am a super fan of Manchester City in Premier League. Kudos to The Treble🏆 🏆 🏆

2. I am proud that I have graudated from the competition class at Hangzhou No.2 High school, where I make friends with so many talented students and prestigious teachers.

3. It is worth mentioning that Rui is my best friend and has motivated me forward for over ten years as my role model. Best wishes and good luck!

Updated at Dec. 2023

Thanks Jon Barron for this amazing template.