Heyuan Li

LI Heyuan

I am a Ph.D. student at The Chinese University of Hong Kong, Shenzhen, working on human-centric 3D computer vision and graphics, advised by Prof. HAN Xiaoguang. Previously, I obtained my M.S. from National University of Singapore, advised by Prof. Robby T. Tan. I received my Bachelor's degree from University of Electronic Science and Technology of China.

I believe simple is better than complex.

I (try to) practice Slow Science. Slow is faster than fast.

Email / Twitter / Github

Research

My research goal is to develop a system that produces and drives high-fidelity 3D avatars in real-time using limited cost for everyone. My current research focus is on the generalizability and robustness of NeRF/3DGS-based head avatars learned from large-scale images.

SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representation
Heyuan Li, Ce Chen, Tianhao Shi, Yuda Qiu, Sizhe An, Guanying Chen, Xiaoguang Han
ECCV, 2024 (Oral Presentation, top 2.3%)
project page / arXiv / video / code

Achieve 3D full-head synthesis without mirroring-face and multiple-face artifacts via spherical tri-plane representation and view-image consistency loss.

Zero-shot Real Facial Attribute Separation and Transfer at Novel Views
Dingyun Zhang, Heyuan Li, Juyong Zhang
CVM, 2024
paper

A model that enables real-time and zero-shot attribute separation of a given real face, allowing attribute transfer and rendering at novel views without the aid of multi-view information.

DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment
Heyuan Li, Bo Wang, Yu Cheng, Mohan Kankanhalli, Robby T. Tan
CVPR, 2023
project page / arXiv / video / code

Infer 3D face reconstruction in both image space and model space to achieve high robustness and accuracy.

Project

	Detailed 3D Face Reconstruction Reconstruct a detailed 3D face from a single image through self-supervised learning and differentiable rendering-based optimization.
	Cloth Simulation via Deep Learning Use neural networks to represent cloth, external objects, and the environment, and conduct a learning-based cloth simulation.
	Vehicle Trajectory Forecasting Trajectory Forecasting with Neural Networks: An Empirical Evaluation and A New Hybrid Model TITS, 2020 Conduct the most comprehensive evaluation of various models proposed for time series data prediction on vehicle trajectory forecasting task, and propose a hybrid model that combines the merits of MLP and LSTM.
Undergraduate Thesis	Gradual Knowledge Distillation Video-based Human Action Detection. Undergraduate Degree Thesis, 2020 Gradually distill knowledge from higher-precision model to lower-precision and finally binary model to alleviate the performance deterioration in Quantization.

The website template was borrowed from source code.