Hao Zhu ("朱昊" in Chinese)

Hao Zhu is currently researcher at SenseTime Research, where he works on AIGC and Neural Rendering.

He received his master degree from Anhui University and is also a joint master student at CRIPAC, CASIA, supervised by Prof. Ran He and Prof. Aihua Zheng.

Please feel free to contact me through email if you have any questions.

Email  /  Google Scholar  /  Github

[Jul 2022] 1 paper was accepted by ECCV 2022. ^new

[Jul 2021] Join SenseTime as a fulltime researcher working on generative models and neural rendering. If you are interested in a research internship position, please contact us.

[Oct 2020] 1 paper on face swapping was accepted by NeurIPS 2020.

[Mar 2020] 1 paper on talking face was accepted by IJCAI 2020.

[Sep 2018] Start my graduate study and research at Anhui University and CRIPAC CASIA.

I'm interested in machine learning, computer vision, and neural rendering. Much of my research is about high-quality generative models.

A large-scale, high-quality, and diverse video dataset with rich facial attribute annotations. CelebV-HQ contains 35,666 video clips with the resolution of 512x512 at least. All clips are labeled manually with 83 facial attributes, covering appearance, action, and emotion.

we provide a comprehensive survey of recent audio-visual learning development.

A new identity swapping algorithm with large differences in appearance for forgery detection.

A novel arbitrary talking face generation framework by discovering the audio-visual coherence via the proposed Asymmetric Mutual Information Estimator (AMIE).

ACF Outstanding Master's Thesis. 2021

Outstanding Master's Graduate, Anhui Province, China. 2021

National Scholarship, AHU. 2020.

Template credits: Jon Barron