Chong Bao

I am a Ph.D. student (2020-now) at the State Key Lab of CAD&CG, Zhejiang University, advised by Prof. Guofeng Zhang and Prof. Zhaopeng Cui. During my Ph.D., I work closely with Yinda Zhang. I used to visit Computer Vision and Geometry Group at ETH Zürich, advised by Marc Pollefeys.

My research interests are in 3D computer vision and AR/VR, specifically neural rendering, structure from motion, and human avatar.

I will graduate in 2025 and am looking for a job in academia or industry.

Email / Google Scholar / Github

Research

	Free360: Layered Gaussian Splatting for Unbounded 360-Degree View Synthesis from Extremely Sparse and Unposed Views Chong Bao, Xiyu Zhang, Zehao Yu, Jiale Shi, Guofeng Zhang, Songyou Peng, Zhaopeng Cui CVPR, 2025 project page / arXiv / video / code We propose a new GS with video diffusion model for novel view synthesis and surface reconstruction from extremely sparse(3-4), unposed images in unbounded 360 scenes.
	LookCloser: Frequency-aware Radiance Field for Tiny-Detail Scene Xiaoyu Zhang, Weihong Pan, Chong Bao, Xiyu Zhang, Xiaojun Xiang, Hanqing Jiang, Hujun Bao, CVPR, 2025 project page / arXiv / code We introduce a novel frequency-aware framework for view synthesis that simultaneously captures the overall scene structure and high-definition details within a single NeRF model.
	GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image Chong Bao, Yinda Zhang, Yuan Li, Xiyu Zhang, Bangbang Yang, Hujun Bao, Marc Pollefeys, Guofeng Zhang, Zhaopeng Cui CVPR*, 2024 project page / arXiv / video / code We present a generic approach to edit 3D avatars in various volumetric representations from a single perspective.
	Mirror-NeRF: Learning Neural Radiance Fields for Mirrors with Whitted-Style Ray Tracing Junyi Zeng, Chong Bao, Rui Chen, Zilong Dong, Guofeng Zhang, Hujun Bao, Zhaopeng Cui MM, 2023 project page / arXiv / video / code We present a novel neural rendering framework, which is able to learn accurate geometry and reflection of the mirror and support various scene manipulation applications.
	IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View Synthesis Weicai Ye, Shuo Chen, Chong Bao, Hujun Bao, Marc Pollefeys, Zhaopeng Cui, Guofeng Zhang ICCV, 2023 project page / arXiv / code We introduce intrinsic decomposition into the NeRF-based neural rendering method and can perform editable novel view synthesis in room-scale scenes.
	SINE: Semantic-driven Image-based NeRF Editing with Prior-guided Editing Field Chong Bao, Yinda Zhang, Bangbang Yang, Tianxing Fan, Zesong Yang, Hujun Bao, Guofeng Zhang, Zhaopeng Cui CVPR*, 2023 project page / arXiv / video / code We present a novel semantic-driven NeRF editing approach, which enables users to edit a neural radiance field with a single image.
	EC-SfM: Efficient Covisibility-based Structure-from-Motion for Both Sequential and Unordered Images Zhichao Ye, Chong Bao, Xin Zhou, Haomin Liu, Hujun Bao, Guofeng Zhang TCSVT, 2023 paper / arXiv / code We present an efficient covisibility-based incremental SfM and exploit covisibility and registration dependency to describe the image connection
	NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editing Bangbang Yang, Chong Bao, Junyi Zeng, Hujun Bao, Yinda Zhang, Zhaopeng Cui, Guofeng Zhang ECCV, 2022 (Oral Presentation) project page / arXiv / video / code We present a novel mesh-based implicit field with disentangled geometry and texture codes on mesh vertices, which facilitates a set of editing functionalities.
	Crossview Mapping with Graph-based Geolocalization on City-Scale Street Maps Zhichao Ye, Chong Bao, Xinyang Liu, Hujun Bao, Zhaopeng Cui, Guofeng Zhang ICRA, 2022 paper We present a low-cost mapping solution that is able to refine and align the monocular reconstructed point cloud given a public street map.
	ARCargo: Multi-Device Integrated Cargo Loading Management System with Augmented Reality Tianxiang Zhang, Chong Bao, Hongjia Zhai, Jiazhen Xia, Weicai Ye, Guofeng Zhang CyberSciTech*, 2021 paper / video We present a multi-device integrated cargo loading management system with AR, which monitors cargoes by fusing perceptual information from multiple devices in real-time.

Experiences

	Student Researcher Google AR 2025.03-now
	Visiting Student Computer Vision and Geometry Lab, ETH Zürich supervised by Marc Pollefeys 2023.09-2024.09
	Research Intern Multi-sensor Fusion Localization Group, Sensetime 2020.07-2020.09
	Research Intern(Star of Tomorrow) Internet Graphics Group, Microsoft Research Asia(MSRA) 2020.04-2020.07

Projects

ARCT
Ziyang Zhang, Chong Bao, Hai Li,
First prize in China Mobile Application Innovation Competition, held by Apple. , 2021
appstore

We develop a platform realizing augmented urban reality based on scene localization.

Design and source code from Jon Barron's website