Weizhe Liu

Researcher at ByteDance

Shanghai, Shanghai, China
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Summary

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Senior
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Top School
Weizhe Liu is a researcher specializing in generative AI for image, video, and 3D content, currently based at ByteDance with 11 years of experience across industry and academia. He earned a PhD in Computer Vision from EPFL, where his thesis focused on human-centered scene understanding and crowd counting, and has held research roles at Tencent, Microsoft, and Amazon applying self-supervised and semi-supervised methods to real-world vision problems. Comfortable moving between foundational research and applied systems, he has a track record in mixed reality, semantic segmentation, and lightweight deep learning for mobile. Fluent in both Western and Chinese research ecosystems, he leverages multidisciplinary training in communication systems and electronic engineering to bridge theory and production. Notably, his career blends deep academic rigor with industry-driven GenAI deployment experience, making him adept at turning cutting-edge vision research into scalable products.
code11 years of coding experience
job3 years of employment as a software developer
bookBachelor of Engineering (BE), Electronic Information Engineering, Bachelor of Engineering (BE), Electronic Information Engineering at University of Electronic Science and Technology
bookMaster's degree, Communication Systems, Master's degree, Communication Systems at Ecole polytechnique fédérale de Lausanne
bookDoctor of Philosophy - PhD, Computer Vision, Doctor of Philosophy - PhD, Computer Vision at EPFL (École polytechnique fédérale de Lausanne)
bookVisiting Scholar, Computer vision, Visiting Scholar, Computer vision at University of California, Los Angeles
languagesEnglish, Chinese, French
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Github Skills (15)

computer-vision10
crowd10
optical-flow10
counting10
siggraph10
deep-learning5
pytorch5
localization3
detectors2
adaptation2
expert2
neural-network1
scene1
optimization1
bag1

Programming languages (2)

Jupyter NotebookPython

Github contributions (5)

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weizheliu/People-Flows

Nov 2020 - Aug 2021

The code for our ECCV 2020 paper: Estimating People Flows to Better Count Them in Crowded Scenes
Contributions:12 commits, 4 PRs, 11 pushes in 8 months
flowseccvoptical-flowestimatingcomputer-vision
Contributions:18 pushes, 1 branch in 4 years 4 months
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