Yu-Jhe Li (李宇哲)

I'm currently an Applied Research Scientist at Adobe Firefly. I was a Research Scientist at Microsoft. I obtained my Doctor of Philosophy (Ph.D.) from Electrical and Computer Engineering at Carnegie Mellon University (CMU) under the guidance of Prof. Kris Kitani. Prior to my doctoral studies, I worked as a research associate with Kris Kitani at the Robotics Institute for one additional year. During my Ph.D. study, I have had the opportunity to spend two memorable summers with Meta Research, and one wonderful summer with Adobe Research.

In the past, I completed my Master of Science (M.Sc.) degree at National Taiwan University (國立台灣大學), where I was supervised by Prof. Yu-Chiang Frank Wang in the Vision and Learning Lab (VLL). I earned my Bachelor of Science (B.S.) degree from National Tsing Hua University (國立清華大學).

yujhe.jack [AT] gmail.com
Email  /  CV (Dec 2023)  /  Google Scholar  /  Github  /  Twitter

We're looking for research interns to work on 3D object control for image generation (diffusion) with LLM/VLM/MLLM models!
Contact me if you are interested.

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News

  • Feb. 2024:   One paper is accepted to CVPR 2024.
  • Aug. 2023:   I successfully defended my PhD!
  • Feb. 2023:   One paper is accepted to CVPR 2023.
  • Feb. 2023:   One paper is accepted to ICASSP 2023 special track.
  • Aug. 2022:   Received Qualcomm Innocation Fellowship (only 19 teams in US, see this)
  • Jul. 2022:   One paper is accepted to ECCV 2022.
  • Mar. 2022:   Two papers are accepted to CVPR 2022.
  • Research

    My research interests span the fields of Machine Learning (ML) and Computer Vision (CV), particularly:

  • Visual representation learning in machine perception (object detection, segmentation, tracking, re-identification).
  • Unsupervised domain adapted learning and data/label efficiency learning in machine perception.
  • Cross-modality visual representation learning for machine generation.
  • Publications (selected)
    clean-usnob Flexible Depth Completion for Sparse and Varying Point Densities
    Jinhyung Park, Yu-Jhe Li, Kris Kitani
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
    clean-usnob Multi-Person 3D Pose Estimation from Multi-View Uncalibrated Depth Cameras
    Yu-Jhe Li, Yan Xu, Rawal Khirodkar, Jinhyung Park, Kris Kitani
    Preprint. Arxiv, 2024
    ArXiv
    clean-usnob Domain Adapted Visual Representation Learning for Machine Perception
    Yu-Jhe Li
    Ph.D. Thesis, Carnegie Mellon University, 2023
    Committee members: Kris Kitani, Matthew O'Toole, Jun-Yan Zhu, Deva Ramanan
    Paper
    clean-usnob Azimuth Super-Resolution for FMCW Radar in Autonomous Driving
    Yu-Jhe Li, Shawn Hunt, Jinhyung Park, Matthew O'Toole, Kris Kitani
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
    Paper/ Dataset & Code
    clean-usnob 3D-CLFusion: Fast Text-to-3D Rendering with Contrastive Latent Diffusion
    Yu-Jhe Li, Tao Xu, Ji Hou, Bichen Wu, Xiaoliang Dai, Albert Pumarola, Peizhao Zhang, Peter Vajda, Kris Kitani
    Preprint. Arxiv 2023
    ArXiv
    clean-usnob ST-MVDNet++: Improve Vehicle Detection with Lidar-Radar Geometrical Augmentation via Self-Training
    Yu-Jhe Li, Matthew O'Toole, Kris Kitani
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
    Paper
    clean-usnob 3D-Aware Encoding for Style-based Neural Radiance Fields
    Yu-Jhe Li, Tao Xu, Bichen Wu, Ningyuan Zheng, Xiaoliang Dai, Albert Pumarola, Peizhao Zhang, Peter Vajda, Kris Kitani
    Preprint. Arxiv 2022
    ArXiv
    clean-usnob Domain Adaptive Hand Keypoint and Pixel Localization in the Wild
    Takehiko Ohkawa, Yu-Jhe Li, Qichen Fu, Ryosuke Furuta, Kris M. Kitani, and Yoichi Sato
    European Conference on Computer Vision (ECCV), 2022
    Arxiv
    clean-usnob Cross-Domain Adaptive Teacher for Object Detection
    Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma, Yen-Cheng Liu, Kan Chen, Bichen Wu, Zijian He, Kris Kitani, Peter Vajda
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    Project Page/ Paper/ Code
    clean-usnob Modality-Agnostic Learning for Radar-Lidar Fusion in Vehicle Detection
    Yu-Jhe Li, Jinhyung Park, Matthew O'Toole, Kris Kitani
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    Paper
    Visio-Temporal Attention for Multi- Camera Multi-Target Association.
    Yu-Jhe Li, Xinshuo Weng, Yan Xu, Kris Kitani
    IEEE International Conference on Computer Vision (ICCV), 2021
    CVF Paper
    Wide-Baseline Multi-Camera Calibration using Person Re-Identification
    Yan Xu, Yu-Jhe Li, Xinshuo Weng, Kris Kitani
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
    CVF Paper
    Learning Shape Representations for Person Re-Identification under Clothing Change
    Yu-Jhe Li, Xinshuo Weng, Kris Kitani
    Winter Conference on Applications of Computer Vision (WACV), 2021
    ArXiv (old version)/ CVF Paper
    clean-usnob Transforming Multi-Concept Attention into Video Summarization
    Yen-Ting Liu, Yu-Jhe Li, Yu-Chiang Frank Wang
    Asian Conference on Computer Vision (ACCV), 2020
    ArXiv/ CVF Paper
    clean-usnob Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond
    Yu-Jhe Li*, Yun-Chun Chen*, Yen-Yu Lin, Yu-Chiang Frank Wang
    (* indicates equal contribution)
    Preprint. Arxiv 2020
    ArXiv
    clean-usnob Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation
    Yu-Jhe Li, Ci-Siang Lin, Yan-Bo Lin, Yu-Chiang Frank Wang
    IEEE International Conference on Computer Vision (ICCV), 2019
    ArXiv/ CVF Paper/ Code
    clean-usnob Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification
    Yu-Jhe Li*, Yun-Chun Chen*, Yen-Yu Lin, Xiao-fei Du, Yu-Chiang Frank Wang (*indicates equal contribution)
    IEEE International Conference on Computer Vision (ICCV), 2019
    ArXiv/ CVF Paper
    clean-usnob Spot and Learn: A Maximum-Entropy Image Patch Sampler for Few-Shot Classification
    Wen-Hsuan Chu, Yu-Jhe Li, Jing-Cheng Chang, Yu-Chiang Frank Wang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
    CVF Paper
    clean-usnob Learning Resolution-Invariant Deep Representations for Person Re-Identification
    Yu-Jhe Li*, Yun-Chun Chen*, Xiao-fei Du, Yu-Chiang Frank Wang (*indicates equal contribution)
    AAAI Conference on Artificial Intelligence (AAAI), 2019   (Oral Presentation)
    ArXiv/ AAAI Paper
    clean-usnob Deep Reinforcement Learning for Playing 2.5D Fighting Games
    Yu-Jhe Li*, Hsin-Yu Chang*, Yu-Jing Lin, Po-Wei Wu, Yu-Chiang Frank Wang (*indicates equal contribution)
    IEEE International Conference on Image Processing (ICIP), 2018
    ArXiv/ IEEE Paper/ Code
    clean-usnob Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification
    Yu-Jhe Li, Fu-En Yang, Yen-Cheng Liu, Yu-Ying Yeh, Xiaofei Du, Yu-Chiang Frank Wang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018
    ArXiv/ Paper/ Code
    Professional Activities
    Reviewer or program committee:

    ICLR 2023, CVPR 2023
    ICLR 2022, CVPR 2022, ECCV 2022, NeurIPS 2022
    AAAI 2021, WACV 2021, CVPR 2021, ICCV 2021
    CVPR 2020, ECCV 2020, ACCV 2020
    Education Experiences
    Ph.D., Electrical and Computer Engineering
    Carnegie Mellon University
    Pittsburgh, PA
    Sep. 2020 - Aug. 2023
    Sep. 2019 - Aug. 2020 (Research Associate @ Robotics Institute)
    M.S., Communication Engineering (data science track)
    National Taiwan University
    Taipei, Taiwan
    Sep. 2017 - Jan. 2019
    B.S., Electrical Engineering and Computer Science
    National Tsing Hua University
    Taipei, Taiwan
    Sep. 2013 - Jan. 2017
    Work Experiences
    Applied Research Scientist
    Adobe
    San Jose, CA
    Apr. 2024 - Current
    Research Scientist
    Microsoft
    Redmond, WA
    Dec. 2023 - Apr. 2024
    Research Intern
    Adobe
    San Jose, CA
    May. 2023 - Nov. 2023
    Research Intern
    Meta
    Burlingame, CA
    May. 2022 - Dec. 2022
    Research Intern
    Facebook (now Meta)
    Menlo Park, CA
    May. 2021 - Aug. 2021
    Software Engineer Intern
    Trend Micro
    Taipei, Taiwan
    July. 2017 - Aug. 2017
    College Misc Experiences
    Exchange Student
    University of Minnesota - Twin Cities
    Minneapolis, MN, USA
    Aug. 2016 - Dec. 2016
    Fall semester
    Exchange Student
    Fudan University
    Shanghai, China
    July. 2015 - Aug. 2015
    Summer
    Exchange Student
    Tsinghua University
    Beijing, China
    July. 2014 - Aug. 2014
    Summer