About Me

I am a second-year PhD student at UT Austin, advised by Prof. Kristen Grauman and Prof. Alex Dimakis. My research lies in Machine Learning and Computer Vision, specifically in the following topics:

• Video understanding and representation Learning
• Deep generative models
• Designing new architectures for real-world machine learning system

Publications

• HOI-Swap: Swapping Objects in Videos with Hand-Object Interaction Awareness
  Zihui Xue, Mi Luo, Changan Chen, Kristen Grauman
  In Advances in Neural Information Processing Systems, NeurIPS 2024.
  [PDF][Project]

• 4DIFF: 3D-Aware Diffusion Model for Third-to-First Viewpoint Translation
  Feng Cheng*, Mi Luo*, Huiyu Wang, Alex Dimakis, Lorenzo Torresani, Gedas Bertasius, Kristen Grauman
  In 2024 European Conference on Computer Vision, ECCV 2024.
  [PDF][Project]

• Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos
  Mi Luo, Zihui Xue, Alex Dimakis, Kristen Grauman
  In 2024 European Conference on Computer Vision, ECCV 2024.
  [PDF][Project]

• Ego-Exo4D: Understanding Skilled Human Activity from First-and Third-Person Perspectives
  Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, …, Mi Luo, …, Pablo Arbelaez, Gedas Bertasius, David Crandall, Dima Damen, Jakob Engel, Giovanni Maria Farinella, Antonino Furnari, Bernard Ghanem, Judy Hoffman, C. V. Jawahar, Richard Newcombe, Hyun Soo Park, James M. Rehg, Yoichi Sato, Manolis Savva, Jianbo Shi, Mike Zheng Shou, Michael Wray
  In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024.
  [PDF][Project][Overview][Video]

• MetaFormer Baselines for Vision
  Weihao Yu, Chenyang Si, Pan Zhou, Mi Luo, Yichen Zhou, Jiashi Feng, Shuicheng Yan, Xinchao Wang
  IEEE Transactions on Pattern Analysis and Machine Intelligence, T-PAMI 2023.
  [PDF][Project]

• MetaFormer is Actually What You Need for Vision
  Weihao Yu, Mi Luo, Pan Zhou, Chenyang Si, Yichen Zhou, Xinchao Wang, Jiashi Feng, Shuicheng Yan
  In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022. (Oral)
  [PDF][Project]
  

• Architecture Personalization in Resource-constrained Federated Learning
  Mi Luo, Fei Chen, Zhenguo Li, Jiashi Feng
  In NFFL Workshop, NeurIPS 2021. (Selected as outstanding paper, acceptance rate: 9%)
  [PDF]
  

• No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
  Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng
  In Advances in Neural Information Processing Systems, NeurIPS 2021.
  [PDF]
  

• MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection
  Mi Luo, Fei Chen, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Jiashi Feng, Zhenguo Li
  In Proceedings of The Web Conference, WWW 2020.
  [PDF]

• Federated Meta-Learning with Fast Convergence and Efficient Communication
  Fei Chen, Mi Luo, Zhenhua Dong, Zhenguo Li, Xiuqiang He
  arXiv, 2019.
  [PDF]

Research Experiences

• Menlo Park, Aug 2024 - Present

  FAIR, Meta AI
  Research Intern, Advisor: Dr. Yuan-Ting Hu

• Singapore, Sep 2021 - Apr 2022

  SEA AI Lab (SAIL)
  Research Intern, Advisor: Prof. Shuicheng Yan

• Singapore, Aug 2020 - Aug 2021

  National University of Singapore
  Research Assistant, Advisor: Prof. Jiashi Feng

• Hong Kong, May 2019 - Oct 2019

  Huawei Noah’s Ark Lab
  Research Intern, Advisor: Dr. Zhenguo Li

Professional Service

• Conference Reviewer: CVPR 2023 - 2024, ECCV 2024, ICCV 2023, ACCV 2024, NeurIPS 2023-2024, ICLR 2024-2025, ICML 2024, AISTATS 2022 - 2025, AAAI 2025
  
• Journal Reviewer: IEEE Transactions on Knowledge and Data Engineering (TKDE), Transactions on Machine Learning Research (TMLR)
  
• Teaching Assistant: EE2211 (Introduction to Machine Learning), CG3207 (Computer Architecture)