Hao Ju (鞠豪 in Chinese) I am a first-year second-year Ph.D. student at University of Macau, supervised by Dr. Shaofei Huang, Dr. Hu Zhang, and Prof. Zhedong Zheng. Previously, I received my Bachelor’s and Master’s degrees from Dalian University of Technology in 2021 and 2024, supervised by Dr. Pengyu Zhang, Prof. Xu Jia and Prof. Dong Wang. I am interested in Computer Vision, Embodied AI and related topics. 📧 Email / 🎓 Scholar 🌟 Highlight: I am currently seeking a long‑term research internship opportunity. Please feel free to contact me if you have an opportunity!

News

• 2026‑01: Passed PhD Qualifying Examination @ UM.
• 2026‑01: (First author) One paper on event-based lip reading is accepted by ACM TOMM.
• 2025‑06: (First author) One paper on cross‑view geo‑localization is accepted by ICCV 2025.
• 2024‑09: (Equal contribution) One paper on event‑assisted blurry image unfolding is accepted by IEEE TNNLS.
• 2024‑07: (Equal contribution) One paper on event‑assisted blurry image unfolding is accepted by IEEE TIP.

Research

Event-based Lip Reading with Triplane Fusion Network Authors: Hao Ju, Zhedong Zheng, Xu Zheng, Wenyue Chen, Lin Wang, Dong Wang, Huchuan Lu, Xu Jia ACM TOMM Paper (coming soon)  /  Code (coming soon) We leverage the high temporal resolution of event data and process event stream in a triplane manner.

Video2BEV: Transforming Drone Videos to BEVs for Video‑based Geo‑localization Authors: Hao Ju*, Shaofei Huang*, Si Liu, Zhedong Zheng ICCV 2025 (* denotes equal contribution) Paper  /  Code We resort to the multi‑view nature of drone‑view videos and transform videos to Bird’s‑Eye View for video‑based geo‑localization.

Event‑Assisted Recurrent Network for Arbitrary‑Temporal‑Scale Blurry Image Unfolding Authors: Pengyu Zhang*, Hao Ju*, Weihua He, Yaoyuan Wang, Ziyang Zhang, Shengming Li, Dong Wang, Huchuan Lu, Xu Jia IEEE TNNLS 2024 (* denotes equal contribution) PDF / We propose an event‑assisted blurry image unfolding framework that can work across arbitrary temporal scales with the help of event streams.

Event‑Assisted Blurriness Representation Learning for Blurry Image Unfolding Authors: Pengyu Zhang*, Hao Ju*, Lei Yu, Weihua He, Yaoyuan Wang, Ziyang Zhang, Qi Xu, Shengming Li, Dong Wang, Huchuan Lu, Xu Jia IEEE TIP 2024 (* denotes equal contribution) PDF / We propose to implicitly model blur in an image by computing blurriness representation from event streams and integrate blurriness into the unfolding network.

Education

• 2024‑09 – Now: Ph.D. student, Computer Science, University of Macau
• 2021‑06 – 2024‑06: M.S., Information & Communication Engineering, Dalian University of Technology
• 2017‑09 – 2021‑06: B.S., Information & Communication Engineering, Dalian University of Technology

Interests

• Sports:

  • Basketball

    • Was a student athlete majored in basketball during primary and middle school and retired after injury

    • Fan of CBA

      • Home team: ZheJiang Lions, ShanDong Hi‑Speed
      • Stan: Yanhao Zhao, Minghui Sun, Xining He

    • Was a fan of NBA

      • Home team: Spurs without No. 2
      • Stan: Manu Ginóbili, Boris Diaw

  • Bodybuilding

• Music: Khalil Fong, David Tao, Jonathan Lee

• Film & TV: Let the Bullets Fly, Crazy Stone, Crazy Racer, Homeland

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