Tao Hu (胡涛)

Postdoc Research Fellow,
S-Lab, College of Computing and Data Science, Nanyang Technological University, Singapore

Ph.D., Department of Computer Science, University of Maryland, College Park, USA

Email: tao.hu [at] ntu.edu.sg, taohu [at] umd.edu

Google Scholar | GitHub | Twitter

College of Computing and Data Science, Nanyang Technological University, Singapore

Research Fellow, Jun. 2023 ~ present

Advisor: Prof. Ziwei Liu
Affiliated: S-Lab and MMLab@NTU directed by Prof. Chen Change Loy.

Department of Computer Science, University of Maryland, College Park, USA

Ph.D., Aug. 2018 ~ Jun. 2023

Supervisor: Prof. Matthias Zwicker

3DV Lab, Tsinghua University, Beijing, China

Research Intern, Apr. 2021 ~ Nov. 2021

Supervisor: Prof. Yebin Liu

Graphics, Vision & Video Group, Max Planck Institute for Informatics, Saarbrücken, Germany

Research Intern, Mar. 2020 ~ Sep. 2020

Supervisor: Prof. Christian Theobalt

Shanghai AI Lab, Shanghai, China

Research Intern, Apr. 2023 ~ Jun. 2023

Supervisor: Prof. Ziwei Liu

Intelligent Creation Lab, ByteDance Inc USA, Remote

Research Intern, Dec. 2021 ~ Jul. 2022

Supervisor: Dr. Hongyi Xu, Dr. Linjie Luo

Speech Group, Microsoft Research Asia (MSRA), Beijing, China

Research Intern, Jun. 2017 - Nov. 2017

Supervisor: Dr. Kai Chen

FashionEngine: Interactive 3D Human Generation and Editing via Multimodal Controls.

Tao Hu, Fangzhou Hong, Zhaoxi Chen, Ziwei Liu.
arXiv:2404.01655, 2024
[Project Page] [Video] [arXiv]
→ The first work that constructs an interactive 3D human generation and editing system with multimodal controls (e.g., texts, images, hand-drawing sketches) in a unified framework.

HumanLiff: Layer-wise 3D Human Generation with Diffusion Model.

Shoukang Hu, Fangzhou Hong, Tao Hu , Liang Pan, Weiye Xiao, Haiyi Mei, Lei Yang, Ziwei Liu
arXiv:2308.09712, 2023
[Paper] [Project Page] [Code]
→ A diffusion-based approach for layer-wise 3D human generation.

StructLDM: Structured Latent Diffusion for 3D Human Generation.

Tao Hu, Fangzhou Hong, Ziwei Liu.
European Conference on Computer Vision (ECCV 2024)
[Project Page] [Video] [Code] [arXiv] [Media Coverage] [Media Coverage in Chinese: 1, 2]
→ A new paradigm for 3D human generation from 2D image collections, with 3 key designs: a structured 2D latent space, a structured auto-decoder, and a structured latent diffusion model.

SurMo: Surface-based 4D Motion Modeling for Dynamic Human Rendering.

Tao Hu, Fangzhou Hong, Ziwei Liu.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2024)
[Paper] [Project Page] [Video] [Code] [Media Coverage in Chinese: Media Heart, SenseTime Research ]
→ A new paradigm for learning dynamic human rendering from videos by jointly modeling the temporal motion dynamics and human appearances in a unified framework based on a novel surface-based triplane.

HVTR++: Image and Pose Driven Human Avatars using Hybrid Volumetric-Textural Rendering.

Tao Hu, Hongyi Xu, Linjie Luo, Tao Yu, Zerong Zheng, He Zhang, Yebin Liu, Matthias Zwicker.
IEEE Transactions on Visualization and Computer Graphics (TVCG 2023)
[Paper] [Project Page] [Video] [Code]
→ A virtual teleportation system using sparse view cameras based on a novel texel-aligned multimodal representation.

HVTR: Hybrid Volumetric-Textural Rendering for Human Avatars.

Tao Hu, Tao Yu, Zerong Zheng, He Zhang, Yebin Liu, Matthias Zwicker.
International Conference on 3D Vision (3DV 2022)
[Paper] [Project Page] [Video] [Poster] [arXiv] [Code]
→ The first work that combines classical volumetric rendering with probabilistic generative models for efficient and realistic dynamic human rendering.

EgoRenderer: Rendering Human Avatars from Egocentric Camera Images.

Tao Hu, Kripasindhu Sarkar, Lingjie Liu, Matthias Zwicker, Christian Theobalt.
IEEE International Conference on Computer Vision (ICCV 2021)
[Paper] [Project Page] [Video] [Poster] [arXiv] [Media Coverage: SCIENCE & TECHNOLOGY NEWS]
→ A mobile virtual teleportation system integrating mobile motion capture and free-view rendering in a egocentric setup.

Learning to Generate Dense Point Clouds with Textures on Multiple Categories.

Tao Hu, Geng Lin, Zhizhong Han, Matthias Zwicker.
IEEE Winter Conference on Applications of Computer Vision (WACV 2021)
[Paper] [Code] [arXiv]
→ Extend the multi-view representation for generalizable geometry/texture reconstructions from single RGB images.

3D Shape Completion with Multi-view Consistent Inference.

Tao Hu, Zhizhong Han, Matthias Zwicker.
AAAI Conference on Artificial Intelligence (AAAI 2020, Oral, top 10% among accepted papers in 3D vision track)
[Paper] [Code] [arXiv]
→ Introduce a self-supervised multi-view consistent inference technique to enforce geometric consistency for multi-view representation.

Render4Completion: Synthesizing Multi-view Depth Maps for 3D Shape Completion.

Tao Hu, Zhizhong Han, Abhinav Shrivastava, Matthias Zwicker.
IEEE ICCV Geometry Meets Deep Learning Workshop (ICCVW 2019, Oral)
[Paper] [Code] [arXiv]
→ Present multi-view based 3D shape representation with a multi-view completion net for dense 3D shape completion.

A Parallel Video Player Plugin for CryEngine.

Tao Hu, Gangyi Ding, Lijie Li, Longfei Zhang.
Highlights of Sciencepaper, Chinese Journal, May 2016.
→Propose a parallel video player plugin for CryEngine3 for a speedup from 16 FPS to 54 FPS at a large-scale virtual stage with 40 LED screens playing videos simultaneously for digital performance.