Fangjinhua Wang

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Fangjinhua Wang (王方锦华)

I am a final-year Ph.D. student in Computer Science at ETH Zurich, supervised by Prof. Marc Pollefeys. Previously, I obtained a Master’s degree in Robotics at ETH zurich (with distinction) and a Bachelor's degree in Mechatronics Engineering at Zhejiang University (with distinction). I am the recipient of ETH Medal (ETH Zurich, 2021) and Chu Kochen Award (highest honor at Zhejiang University, 2017).

I am on the job market.

Email / Google Scholar / Github / Linkedin / Twitter

Research Overview

My research is motivated by the goal of enabling embodied AI agents to perceive, understand and interact with the physical world as humans. During my PhD, I have been working in the intersection of 3D computer vision and deep learning, including perception of spatial positioning information (visual localization), geometry (3D reconstruction) and appearance (neural rendering).

On the one hand, I focus on efficient algorithms that are computation-friendly for AR/VR/MR/robotics in general settings. On the other hand, I am interested in accurate representation for challenging settings, including large-scale scenes, non-Lambertian surfaces, dynamics and sparse inputs.

Based on the perception of surroundings, I am currently working on understanding and interaction with the physical world, such as open vocabulary scene understanding.

Publications

* denotes equal contribution.

	DepthSplat: Connecting Gaussian Splatting and Depth Haofei Xu, Songyou Peng, Fangjinhua Wang, Hermann Blum, Daniel Barath, Andreas Geiger, Marc Pollefeys In arXiv. Under review Paper / Project Page / Code
	Learning-based Multi-View Stereo: A Survey Fangjinhua Wang, Qingtian Zhu, Di Chang, Quankai Gao, Junlin Han, Tong Zhang, Richard Hartley, Marc Pollefeys In arXiv. Under review* Paper
	UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections Fangjinhua Wang, Marie-Julie Rakotosaona, Michael Niemeyer, Richard Szeliski, Marc Pollefeys, Federico Tombari NeurIPS, 2024 Paper / Project Page / Code (coming soon)
	HSR: Holistic 3D Human-Scene Reconstruction from Monocular Videos Lixin Xue, Chen Guo, Chengwei Zheng, Fangjinhua Wang, Tianjian Jiang, Hsuan-I Ho, Manuel Kaufmann, Jie Song, Otmar Hilliges ECCV, 2024 Paper / Project Page / Code
	GLACE: Global Local Accelerated Coordinate Encoding Fangjinhua Wang, Xudong Jiang, Silvano Galliani, Christoph Vogel, Marc Pollefeys CVPR, 2024 Paper / Project Page / Code
	VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction Yufan Ren, Fangjinhua Wang, Tong Zhang, Marc Pollefeys, Sabine Süsstrunk CVPR, 2023 Paper / Project Page / Code
	IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys CVPR, 2022 Paper / Code
	PatchmatchNet: Learned Multi-View Patchmatch Stereo Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys CVPR, 2021 (Oral Presentation) Paper / Code
	Self-Calibrated Multi-Sensor Wearable for Hand Tracking and Modeling Nikhil Bharadwaj Gosala, Fangjinhua Wang, Zhaopeng Cui, Hanxue Liang, Oliver Glauser, Shihao Wu, Olga Sorkine-Hornung IEEE Transactions on Visualization and Computer Graphics, 2021

Teaching experience

Computer Vision, ETH Zurich, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024
3D Vision, ETH Zurich, Spring 2023, Spring 2024
Introduction to Machine Learning, ETH Zurich, Spring 2021

Work experience

Google (Zurich, Switzerland), 2023
Meta Reality Labs (Redmond, US), 2022
Microsoft Mixed Reality & AI Zurich Lab (Zurich, Switzerland), 2020

Academic service

Journal reviewer: T-PAMI, IJCV, TIP, TVCG, RA-L, TCSVT, CAG, Neural Computing
Conference reviewer: CVPR, NeurIPS, ICCV, ECCV, AAAI, ICLR, ICRA, ACCV

Thanks for the awesome template!