Jiayi Wu

Jiayi Wu

University of Maryland, College Park

👤 Short Bio

Welcome to my academic homepage. I am Jiayi Wu, a Ph.D. student supervised by Prof. Yiannis Aloimonos at PRG (Perception & Robotics Group) Lab, University of Maryland, College Park. My research focuses on computer vision and robotics, specifically in the areas of active vision, field robotics, and underwater 3D vision. Inspired by nature, I am dedicated to creating innovative robot perception systems that challenge existing paradigms and redefine the future of robotics.

My research interest includes:

  • General Environment Vision: Make computer vision systems more robust to the environment (scattering media, bad weather)
  • Low-cost 3D reconstruction and depth estimation in scattering medium
  • Active Vision: Feedback control through vision

Latest CV’s link

📰 News

  • 2022/08/23: Completed the summer internship at Vobile and got a return offer (recommended by Dr. Zhao).

  • 2022/05/23: Joined the team of Dr. Zhao (CTO of Vobile) of Vobile as an audio and video algorithm development engineer (summer internship).

  • 2022/01/10: Join Professor Judge’s Remote Sensing Lab (as Graduate Student Assistant) and be responsible for the development of a large-scale automated generation of 3D plant models.

🎓 Educations

University of Maryland, College Park

University of Florida

Zhejiang Sci-Tech University (ZSTU)

  • B.E. in Mechatronic Engineering ——— Sept. 2017- Jun. 2021
    2021 Outstanding Graduate, Zhejiang Sci-Tech University

📝 Publications

Conference Papers

CAI 2023 (Best Paper Award)
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  • Wu, Jiayi, Yu, Boxiao, Islam, Md Jahidul. 3D Reconstruction of Underwater Scenes using Nonlinear Domain Projection. IEEE CAI (Best Paper Award). 2023
    [IEEE Xplore] [Poster] [Video demo]
ICRA 2023 (has been accepted)
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  • Yu, Boxiao, Wu, Jiayi, Islam, Md Jahidul. UDepth: Fast Monocular Depth Estimation for Visually-guided Underwater Robots. ICRA. 2023, pp. 3116-3123, doi: 10.1109/ICRA48891.2023.10161471.
    [IEEE Xplore] [arXiv] [Code] [pre-print]
  • A. Kaleo Roberts, Kamal Sarabandi, Jasmeet Judge, Alejandro Monsivais-Huertero, Jiayi Wu. VALIDATION OF A FULL-WAVE BACKSCATTER MODEL FOR CORN FIELDS USING MEASUREMENTS FROM A GROUND-BASED SCATTEROMETER. IGARSS. 2023

Journals and Thesis

  • Wu, Jiayi. Low-Cost Depth Estimation and 3D Reconstruction in Scattering Medium. Master’s Thesis. 2023
    [UFDC]

  • A. K. Roberts, J. Wu, A. Monsivais-Huertero, J. Judge, R. C. Moore and K. Sarabandi, Microwave Backscatter Phenomenology of Corn Fields at L-Band Using a Full-Wave Electromagnetic Solver, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-11, 2024, Art no. 2000511, doi: 10.1109/TGRS.2023.3340198.
    [IEEE Xplore]

📖 Patents

📃 Projects

A Collaborative Project
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UDepth

  • A monocular underwater depth estimation pipeline, using RMI as the input space, constructs a lightweight domain projection module, a lightweight CNN feature extraction module, and a lightweight Transformer-based depth estimation network. And the depth estimation network is supervised with knowledge of underwater light attenuation as a prior. The results show that our depth estimation accuracy is close to the SOTA model, and much faster than them.
    This is a collaborative project on underwater depth estimation with Boxiao Yu, a Ph.D. student in RoboPI lab.
    [IEEE Xplore] [arXiv] [Code] [pre-print]
Master's Thesis
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SDU-SfM

  • A fast depth-guided semi-dense underwater 3D reconstruction pipeline without a deep learning model. Underwater image restoration is implemented through RMI channel and underwater imaging model to improve the number of feature matches. Reduce the computational complexity of feature extraction by using the depth map as a mask. In order to achieve higher quality(semi-dense) underwater 3D reconstruction, the depth maps are used as the supervision to refine the 3D point cloud and remove noise.
    This project is my master’s thesis, we have submitted a journal to the IEEE Transactions on Artificial Intelligence (TAI). Here is the video demo.
R&D Internship Project
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Learning-based Infringing Video Retrieval

  • An learning-based infringing video retrieval system based on the fusion of global features and local features. I did a summer internship in the Vobile’s R&D department under the supervision of Dr. Zhao, CTO of Vobile. I built a learning-based infringing video retrieval system based on the fusion of global features and local features. I used Vobile’s video database to train the model, and achieved good performance. Before I ended my internship, I put it together into a python package and organize each component in the system into an easy-to-use python toolkit. I also wrote the manual of the package and a document about future optimization steps to finally handed over to the person who took over the project.

🏭 Job Experience

  • Digital Audio and Video Algorithm Engineer ——— May. 2022- Aug. 2022
    Vobile, Santa Clara, CA, United States.

  • Graduate Student Assistant ——— Jan. 2022- present
    Remote Sensing Laboratory at University of Florida, Gainesville, FL, United States.

🏅 Honors and Awards

SCHOLARSHIPS

  • 2020.12 Zhejiang Government Scholarship
  • 2019.09 First Class School Financial Aid for Overseas Exchange Program
  • 2018.12 Zhejiang Government Scholarship

COMPETITIONS

  • 2021.06 Individual 1st Prize in the National University Graduate Design Competition (Only two people won this award nationwide) 06/2021
  • 2019.10 Provincial 1st Prize of National 3D Digital Innovative Design Competition
  • 2019.09 2nd Prize of National 3dds Competition Classic
  • 2019.06 3rd Prize of The 16th Zhejiang Province Mechanical Design Competition for College Student
  • 2019.04 3rd Prize of The Challenge Cup Extracurricular Academic Works Competition

💬 Academic Services

Reviewer

  • 2023/2024 IEEE International Conference on Robotics and Automation (ICRA)
  • 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • IEEE Journal of Oceanic Engineering (IEEE JOE)