Fangcheng Zhong
Research
With a broad interest in computer graphics, computer vision, 3D machine learning, and applied mathematics, my research spans the entire digital reality pipeline --- from 3D scene acquisition and representation, to rendering and novel 3D displays. I am particularly interested in 1) hyper-realistic 3D imaging and rendering; 2) differentiable graphics; 3) neural representations; and 4) 3D generative modelling.
My PhD work was the first that established an end-to-end 3D imaging and display system that passed a Visual Turing Test.
About Me
I joined the Graphics & Interaction (Rainbow) Group at the University of Cambridge in 2018 as a Marie-Curie ITN Early Stage Researcher as part of the European ITN RealVision Project and completed a PhD in computer science advised by Prof. Rafał Mantiuk in 2021. My PhD was fully funded by the Marie Skłodowska-Curie Fellowship.
I am currently a Postdoctoral Researcher working with Prof. Cengiz Öztireli and an Affiliated Lecturer in the Department of Computer Science and Technology. I am currently teaching a new course in Extended Reality.
I keep my LinkedIn Profile up to date with my full education/work experience.
Teaching
2022-23:
Supervision
2018-19:
2019-20:
- Part IA Introduction to Graphics
- Part IB Further Graphics
- Part II Advanced Graphics and Image Processing
- Part II Computer Vision
- Part II Machine Learning and Bayesian Inference
2020-21:
- Part IA Algorithms
- Part IA Introduction to Graphics
- Part IB Further Graphics
- Part II Advanced Graphics and Image Processing
2021-22:
2022-23:
Selected Publications
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation
Chenliang Zhou, Fangcheng Zhong, Cengiz Oztireli
Proceedings of ACM SIGGRAPH, 2023
D2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video
Tianhao Wu, Fangcheng Zhong, Andrea Tagliasacchi, Forrester Cole, Cengiz Oztireli
Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2022
Dark Stereo: Improving Depth Perception under Low Luminance
Krzysztof Wolski, Fangcheng Zhong, Karol Myszkowski, Rafał K. Mantiuk
ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH), 2022
Kubric: a Scalable Dataset Generator
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam Laradji, Hsueh-Ti (Derek) Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Oztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi
Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Reproducing Reality with a High-Dynamic-Range Multi-Focal Stereo Display
Fangcheng Zhong, Akshay Jindal, Özgür Yöntem, Param Hanji, Simon Watt, Rafał K. Mantiuk
ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH Asia), 2021
Noise-Aware Merging of High Dynamic Range Image Stacks without Camera Calibration
Param Hanji, Fangcheng Zhong, Rafał K. Mantiuk
Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2020
DiCE: Dichoptic Contrast Enhancement for VR and Stereo Displays
Fangcheng Zhong, George Alex Koulieris, George Drettakis, Martin S. Banks, Fredo Durand, Rafał K. Mantiuk
ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH Asia), 2019
Dissertation
Path from Photorealism to Perceptual Realism
Fangcheng Zhong
Contact
Email: fangcheng [dot] zhong [at] cst [dot] cam [dot] ac [dot] uk
Phone: +44 (0)1223 763659
Office: SS13, Computer Laboratory
Address: Computer Laboratory, William Gates Building, 15 JJ Thomson Ave, Cambridge CB3 0FD
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