Ruiqi Wang


ruiqi_w@sfu.ca

Ph.D Student

Simon Fraser University

About Me

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I am a Ph.D student in GrUVi Lab at Simon Fraser University, supervised by Prof. Hao(Richard) Zhang.
I have a board interest in computer vision and graphics with deep learning methods. My current research focuses on real-world understanding and Multi-modal Large Language Models for reasoning tasks.

Before joined SFU, I received my M.S. (with Distinction) in Machine Learning and Computer Vision from The Australian National University, under the supervision of Prof. Stephen Gould in December, 2020. I completed my B.Eng (Cum Laude) in Digital Media Technology at Beijing Normal University in June, 2018, finishing the 4-year program in 3 years.

News

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06/2025
Released Ego-R1 and finished my visiting at NTU, thanks to all the help from my advisors and friends! 🎉
05/2025
Finally made RESAnything public after 6 months, iykyk ... 🥲
03/2025
I am visiting MMLab@NTU advised by Prof. Ziwei Liu. 😎
07/2024
MVP-SEG, the work I did in 2022, is finally accepted to ECCV 2024. 🥹
06/2024
Starting my internship as an Applied Scientist at Amazon Science. 😎

Publications

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Ego-R1: Chain-of-Tool-Thought for Ultra-Long Egocentric Video Reasoning
preprints 2025
Introduced a novel framework for reasoning over ultra-long (i.e., in days and weeks) egocentric videos, which leverages a structured Chain-of-Tool-Thought (CoTT) process orchestrated by an Ego-R1 Agent.
RESAnything: Attribute Prompting for Arbitrary Referring Segmentation
Ruiqi Wang and Hao Zhang
preprints 2025
Presented an open-vocabulary and zero-shot method for arbitrary Referring Expression Segmentation (RES), targeting more general input expressions than those handled by prior works.
AnaMoDiff: 2D Analogical Motion Diffusion via Disentangled Denoising
preprints 2024
Presented a novel diffusion-based method for 2D motion analogies that is applied to raw, unannotated videos of articulated characters.
Active Coarse-to-Fine Segmentation of Moveable Parts from Real Image
ECCV 2024
Introduced the first active learning (AL) framework for high-accuracy instance segmentation of moveable parts from RGB images of real indoor scenes.

Working experience

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Visiting Student (RA II) | Nanyang Technological University
MMLab
2025/03 - 2025/06
Applied Scientist II Intern | Amazon Science
Visual Innovation Team
2024/06 - 2024/10

Student Visiting Scientist | CSIRO's Data61
Imaging and Computer Vision Group
2020/11 - 2021/05

Awards

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  • Ph.D. Research Scholarship, Simon Fraser University, 2023, 2024, 2025
  • Graduate Fellowship, Simon Fraser University, 2023, 2024
  • Bruce Hall Residential Scholarship, The Australian National University, 2019-2020
  • Excellent Graduate Scholarship, Beijing Normal University, 2018
  • Dean's Honour Roll, Beijing Normal University, 2016, 2017, 2018


  • TAs

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    SFU

  • Summer 2023: CMPT 729 Reinforcement Learning, under Prof. Jason Peng.
  • Spring 2023: CMPT 713 Natural Language Processing, under Prof. Angel Chang.
  • ANU

  • S2 2020: COMP1730/COMP6730 Programming for Scientist, under Prof. Patrik Haslum
  • S2 2020: COMP3670/COMP6670 Introduction to Machine Learning, under Prof. Liang Zheng.


  • Services

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  • Conflict of Interest Coordinator, SIGGRAPH ASIA 2024
  • Reviewer, CVPR 2025, ICCV 2025, IJCV 2025, SIGGRAPH ASIA 2025