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Ziyu Chen I'm a master's student at Shanghai Jiao Tong University (SJTU), advised by Prof. Li Song. Previously, I obtained my Bachelor degree from SJTU. I'm fortunate to work under guidance of Prof. Yue Wang at University of Southern California. My research interests include Computer Graphics, Neural Rendering, Scene Reconstruction. Email / Github / Google Scholar / Twitter |
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Publications |
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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 Preprint, 2024 Project Page / Arxiv / Code OmniRe is a holistic framework for dynamic scene reconstruction that provides comprehensive coverage, including static backgrounds, driving vehicles, and non-rigidly moving dynamic actors. |
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360-Degree Panorama Generation from Few Unregistered NFoV Images
Jionghao Wang*, Ziyu Chen*, Jun Ling, Rong Xie, Li Song (* denotes equal contribution) ACM Multimedia, 2023 Paper / Code We proposed a novel diffusion-based pipeline that generates complete 360 panoramas using one or more unregistered NFoV images captured from arbitrary angles. This pipeline not only delivers superior quality panoramas but also offers a broader range of outcomes due to its text-conditioned generation capability. |
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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 Paper / Code Our L-Tracing based reflectance factorization framework produces photo-realistic novel view images with nearly 10x speedup, compared with the same framework applying volumetric integration for light visibility estimation. |
Projects |
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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.). |
Honors & Awards |
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Website template from here |