Yaohui Wang 王耀晖

Ph.D. Inria

I am a Research Scientist at Shanghai AI Laboratory, where I work on large-scale deep generative models. I obtained my PhD from Inria, STARS team focusing on developing learning methods for video generation with my advisors Antitza Dantcheva and Francois Bremond. Before that, I received a M.Sc degree in Machine Learning from Université Paris-Saclay.

I am looking for research interns focusing on deep generative models for videos/3D/images. Feel free to contact me if you are interested.

Research

LaVie: High-Quality Video Generation with Cascaded Latent Diffusion Models
Yaohui Wang*, Xinyuan Chen*, Xin Ma*, Shangchen Zhou, Ziqi Huang, Yi Wang, Ceuyuan Yang, Yinan He, Jiashuo Yu, Peiqing Yang, Yuwei Guo, Tianxing Wu, Chenyang Si, Yuming Jiang, Cunjian Chen, Chen Change Loy, Bo Dai, Dahua Lin^†, Yu Qiao^†, Ziwei Liu^†
arXiv:2309.15103
Paper | Arxiv | Project page | Code

LAC: Latent Action Composition for Skeleton-based Action Segmentation
Di Yang, Yaohui Wang*, Antitza Dantcheva, Quan Kong, Lorenzo Garattoni, Gianpiero Francesca, Francois Bremond. *corresponding author
In Proc. ICCV, Paris, 2023
Paper | Arxiv | Project page | Code

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Yaohui Wang, Yu Qiao, Dahua Lin, Bo Dai
arXiv:2307.04725
Paper | Arxiv | Project page | Code

LEO: Generative Latent Image Animator for Human Video Synthesis
Yaohui Wang, Xin Ma, Xinyuan Chen, Antitza Dancheva, Bo Dai, Yu Qiao
arXiv:2305.03989
Paper | Arxiv | Project page | Code

Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation
Zeyu Lu, Chengyue Wu, Xinyuan Chen, Yaohui Wang, Lei Bai, Yu Qiao, Xihui Liu
arXiv:2304.11829
Paper | Arxiv | Project page | Code

Long-Term Rhythmic Video Soundtracker
Jiashuo Yu, Yaohui Wang, Xinyuan Chen, Xiao Sun, Yu Qiao
In Proc. ICML, Hawaii, 2023
Paper | Arxiv | Project page | Code

Self-supervised Video Representation Learning via Latent Time Navigation
Di Yang, Yaohui Wang, Quan Kong, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca and François Brémond
In Proc. AAAI, Washington, 2023
Paper | Arxiv | Project page | Code

ViA: View-invariant Skeleton Action Representation Learning via Motion Retargeting
Di Yang, Yaohui Wang, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca and François Brémond
arXiv:2209.00065
Paper | Arxiv | Project page | Code

Latent Image Animator: Learning to Animate Images via Latent Space Navigation
Yaohui Wang, Di Yang, Francois Bremond and Antitza Dantcheva
In Proc. ICLR, Virtual, 2022
Paper | Arxiv | Project page | Code

UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition
Di Yang*, Yaohui Wang*, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca and Francois Bremond. *equal contribution
In Proc. BMVC, Virtual, 2021 (Oral)
Paper | Arxiv | Project page | Code

InMoDeGAN: Interpretable Motion Decomposition Generative Adversarial Network for Video Generation
Yaohui Wang, Francois Bremond, and Antitza Dantcheva
arXiv:2101.03049
Arxiv | Project page | Code

Joint Generative and Contrastive Learning for Unsupervised Person Re-identification
Hao Chen*, Yaohui Wang*, Benoit Lagadec, Antitza Dantcheva, and Francois Bremond. *equal contribution
In Proc. CVPR, Virtual, 2021.
Paper | Code
Learning Invariance from Generated Variance or Unsupervised Person Re-identification
In IEEE TPAMI, 2022.
Paper | Code

Selective Spatio-Temporal Aggregation Based Pose Refinement System
Di Yang, Rui Dai, Yaohui Wang, Rupayan Mallick, Luca Minciullo, Gianpiero Francesca, and Francois Bremond
In Proc. WACV, Virtual, 2021.
Paper | Code

G³AN: Disentangling appearance and motion for video generation
Yaohui Wang, Piotr Bilinski, Francois Bremond, and Antitza Dantcheva
In Proc. CVPR, Seattle, US, 2020.
In LUV-CVPR Workshop, Seattle, US, 2020. (Oral Presentation)
Paper | Project page | Code | Video

ImaGINator: Conditional Spatio-Temporal GAN for Video Generation
Yaohui Wang, Piotr Bilinski, Francois Bremond, and Antitza Dantcheva
In Proc. WACV, Aspen, US, 2020.
Paper | Code | Video

A video is worth more than 1000 lies. Comparing 3DCNN approaches for detecting deepfakes
Yaohui Wang and Antitza Dantcheva
In Proc. FG, Buenos Aires, Argentina, 2020.
Paper

From attribute-labels to faces: face generation using a conditional generative adversarial network
Yaohui Wang, Antitza Dantcheva and Francois Bremond
In Proc. ECCV Workshop, Munich, Germany, 2018.
Paper

Comparing methods for assessment of facial dynamics in patients with major neurocognitive disorders
Yaohui Wang, Antitza Dantcheva, Francois Bremond and Piotr Bilinski
In Proc. ECCV Workshop, Munich, Germany, 2018.
Paper

PhD Thesis

Learning to Generate Human Videos
Yaohui Wang
Thesis

Defense Jury:

• George Drettakis (President), Inria Sophia Antipolis, France
• Ivan Laptev, Inria Paris/École normale supérieure, France
• Elisa Ricci, University of Trento, Italy
• Shiguang Shan, Chinese Academy of Sciences, China
• Sergey Tulyakov, Snap Research, USA
• Panayiotis Georgiou, Apple Inc./University of Southern California, USA

Professional activities

Reviewer

SIGGRAPH 2022, CVPR 2022/2021, ECCV 2022/2020, WACV 2020 ...

Teaching

Winter 2021

Deep Learning for Computer Vision, Lecture and TA, MSc of Data Science and Artificial Intelligence, 3IA Cote d'Azur

Winter 2020

Deep Learning for Computer Vision, Lecture and TA, MSc of Data Science and Artificial Intelligence, 3IA Cote d"Azur

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