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Ziyu Chen

Ph.D. Student in Computer Science
Stanford University

Email: ziyuchen@stanford.edu

About Me

I am a first-year PhD student in Computer Science at Stanford University, working in the Stanford Vision and Learning Lab. Previously, I had the privilege of working closely with Prof. Yue Wang at USC as a visiting student in GVL. I was also fortunate to collaborate with Prof. Marco Pavone at Stanford and Dr. Ge Yang at MIT.

Research Interests

Generative Models

Closed-loop Evaluation & Simulation

Dynamic Scene Modeling

Education

Ph.D. Stanford University Present

M.S. Shanghai Jiao Tong University 2025

B.E. Shanghai Jiao Tong University 2022

Updates
    Mar 2025 I am honored to receive the Stanford Graduate Fellowship 🎓 Feb 2025 OmniRe is accepted to ICLR 2025 as Spotlight 🌟 Shout out to Prof. Yue and all my collaborators! OCT 2024 Talk at MIT Visual Computing Seminar, visited beautiful Boston! 🚣 AUG 2024 Released DriveStudio, a 3DGS system for driving reconstruction/simulation! 🚗 SEP 2023 Joined Geometry, Vision, and Learning Lab as a research intern, advised by Prof. Yue Wang!
Publications

The Neverwhere Visual Parkour Benchmark Suite
Ziyu Chen, Haoran Chang, Henghui Bao, Ran Choi, Alan Yu, Ri-Zhao Qiu, Yajvan Ravan, John J. Leonard, Xiaolong Wang, Phillip Isola, Ge Yang †, Yue Wang
Under Review

OmniRe: Omni Urban Scene Reconstruction
Ziyu Chen, Jiawei Yang, Jiahui Huang, Riccardo de Lutio, Janick Martinez Esturo, Boris Ivanovic, Or Litany, Zan Gojcic, Sanja Fidler, Marco Pavone, Li Song, Yue Wang
ICLR 2025 (Spotlight)

360-Degree Panorama Generation from Few Unregistered NFoV Images
Jionghao Wang*, Ziyu Chen*, Jun Ling, Rong Xie, Li Song
(* equal contribution)
ACM Multimedia 2023

L-Tracing Image

L-Tracing: Fast Light Visibility Estimation on Neural Surfaces by Sphere Tracing
Ziyu Chen, Chenjing Ding, Jianfei Guo, Dongliang Wang, Yikang Li, Xuan Xiao, Wei Wu, Li Song
ECCV 2022

Open-source

A 3DGS codebase for dynamic urban scene reconstruction/simulation, supporting multiple popular driving datasets, including: Waymo, PandaSet, ArgoVerse2, KITTI, NuScenes and NuPlan. It also provides different types of Gaussian representations for reconstructing rigid (Vehicles) and non-rigid individuals (Pedestrians, Cyclists, etc.).

Recent Talks
OmniRe: Omni Urban Scene Reconstruction
  • MIT Visual Computing Seminar, Oct, 2024
  • Peking University, Oct, 2024
  • LiAuto, Sept, 2024
Honors & Awards

Stanford Graduate Fellowship, Stanford,2025

National Scholarship, SJTU, 2023

Zhiyuan Honor Scholarship, SJTU, 2018-2022


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