Weiming Ren

I am a Ph.D. student at the Cheriton School of Computer Science, University of Waterloo, supervised by Prof. Wenhu Chen. I am also affiliated with the Vector Institute. My research interests include developing novel algorithms for controllable video generation, image and video editing, and image restoration, as well as designing efficient model architectures and data curation pipelines to enhance large multimodal models (LMMs) for image and video understanding.

Before starting my Ph.D., I received my master’s degree from the Department of Computer Science, University of Toronto, where I was a student in the MSc. in Applied Computing program. I was also a research intern at Samsung AI Centre Toronto, supervised by Dr. Iqbal Mohomed. I received my bachelor’s degrees from Beijing Institute of Technology and the Australian National University.

My Email: w2ren [at] uwaterloo [dot] ca

publications

  1. arXiv 2024
    VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal Augmentation
    Weiming Ren, Huan Yang, Jie Min, Cong Wei, and Wenhu Chen
    arXiv preprint arXiv:2412.00927 2024
  2. arXiv 2024
    OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision
    Cong Wei, Zheyang Xiong, Weiming Ren, Xinrun Du, Ge Zhang, and Wenhu Chen
    arXiv preprint arXiv:2411.07199 2024
  3. NeurIPS 2024
    MMLU-Pro: A More Robust and Challenging Multi-task Language Understanding Benchmark
    Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, and others
    NeurIPS Dataset and Benchmark Track (Spotlight) 2024
  4. TMLR 2024
    Video Diffusion Models: A Survey
    Andrew Melnik, Michal Ljubljanac, Cong Lu, Qi Yan, Weiming Ren, and Helge Ritter
    Transactions on Machine Learning Research (TMLR) 2024
  5. TMLR 2024
    AnyV2V: A Plug-and-Play Framework For Any Video-to-Video Editing Tasks
    Max Ku*, Cong Wei*, Weiming Ren*, Harry Yang, and Wenhu Chen
    *: Equal Contribution
    Transactions on Machine Learning Research (TMLR) 2024
  6. COLM 2024
    StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
    Alex Zhuang, Ge Zhang, Tianyu Zheng, Xinrun Du, Junjie Wang, Weiming Ren, Stephen W Huang, Jie Fu, Xiang Yue, and Wenhu Chen
    Conference on Language Modeling (COLM) 2024
  7. TMLR 2024
    ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation
    Weiming Ren, Harry Yang, Ge Zhang, Cong Wei, Xinrun Du, Stephen Huang, and Wenhu Chen
    Transactions on Machine Learning Research (TMLR) 2024
  8. CVPR 2024
    Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
    Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, and others
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (Oral) 2024
    1. MLHC 2022
      HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding
      Weiming Ren, Ruijing Zeng, Tongzi Wu, Tianshu Zhu, and Rahul G Krishnan
      In Machine Learning for Healthcare Conference 2022

    experiences

    01.ai, Beijing
    Research Intern - Aug. 2023 to present
    Advisor: Dr. Huan Yang
    Samsung AI Center Toronto, Canada
    Research Intern - May. 2022 to Apr. 2023
    Advisor: Dr. Iqbal Mohomed
    The Future Laboratory, Tsinghua University, China
    Research Intern - Nov. 2019 to Feb. 2020
    Advisor: Prof. Yingqing Xu

    education

    University of Waterloo, Canada
    Ph.D. in Computer Science - Sep. 2023 to present
    University of Toronto, Canada
    Master of Science in Applied Computing - Sep. 2021 to Dec. 2022
    Australian National University, Australia
    Bachelor in Advanced Computing (Honours) - Jul. 2019 to Jun. 2021
    Beijing Institute of Technology, China
    Bachelor of Science in Computer Science and Technology - Sep. 2017 to Jun. 2021