Di Qiu

Currently, I work as a research engineer in Google AR.

Prviously I got my PhD from The Chinese University of Hong Kong, and worked as a research intern at Google and SenseTime Research.

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MonoAvatar: Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos

Ziqian Bai, Feitong Tan, Zeng Huang, Kripasindhu Sarkar, Danhang Tang, Di Qiu, Abhimitra Meka, Ruofei Du, Mingsong Dou, Sergio Orts-Escolano, Rohit Pandey, Ping Tan, Thabo Beeler, Sean Fanello, Yinda Zhang
CVPR, 2023

Use a parametric head model equipped with learnable features to do photo-real free view-point rendering.

Modal Uncertainty Estimation via Discrete Latent Representation

Di Qiu, Lok Ming Lui
MICCAI UNSURE workshop, 2021

Learning latent mode hypothesis and their uncertainty estimation for one-to-many mappings.

Towards Geometry Guided Neural Relighting with Flash Photography

Di Qiu, Jin Zeng, Zhanghan Ke, Wenxiu Sun, Chengxi Yang
3DV, 2020

Directional relighting from a single co-located flash image and its depth map.

Inconsistent Surface Registration via Optimization of Mapping Distortions

Di Qiu, Lok Ming Lui
Journal of Scientific Computing, 2020

Simutaneouly finding domain of correspondence and registration by optimizing distortions in the mapping differential.

Deep End-to-End Alignment and Refinement for Time-of-Flight RGB-D Modules

Di Qiu, Jiahao Pang, Chengxi Yang, Wenxiu Sun
ICCV, 2019

Cross-modal flow estimation and Time-of-Flight depth refinement using deep learning.

[code & dataset]
Computing Quasiconformal Folds

Di Qiu, Ka Chun Lam, Lok Ming Lui
SIAM Journal of Imaging Science, 2019

Computing folding and unfolding maps via a generalized form of quasiconformal mapping and crease geometry inference.


This theme is adapted from Jon Barron's page .