Senior Research Scientist, Adobe Research
Adjunct Faculty, CMU
Pittsburgh, PA
Email: xuhuang1995 at gmail dot com
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My name is Xun Huang (pronounced as /shuun hwang/). I am a Senior Research Scientist at Adobe and also an Adjunct Faculty at CMU. My recent research focuses on real-time, interactive, and autoregressive video/world models. I lead the interactive video world model research at Adobe.
I was a researcher at NVIDIA prior to joining Adobe. I developed one of the first text-to-image demo with multimodal control (GauGAN2), coauthored papers that serve as the basis of NVIDIA's text-to-image and text-to-3D foundation models and shipped them into production.
I obtained my PhD in Computer Science from Cornell in 2020, advised by Professor Serge Belongie. During my PhD, I invented Adaptive Instance Normalization (AdaIN) and was the first to demonstrate its effectiveness in generative neural networks. AdaIN became a foundational component of StyleGAN and played a key role in the first working diffusion model. Variants of AdaIN are now used in nearly all state-of-the-art diffusion models. My PhD research was supported by Adobe Research Fellowship (2019), Snap Research Fellowship (2019), and NVIDIA Graduate Fellowship (2018).
ICCV 2025 (Best Paper @ CVPR 2025 T4V Workshop)
Sicheng Mo, Thao Nguyen, Xun Huang, Siddharth Srinivasan Iyer, Yijun Li, Yuchen Liu, Abhishek Tandon, Eli Shechtman, Krishna Kumar Singh, Yong Jae Lee, Bolei Zhou, Yuheng Li
[arXiv] [Project]ECCV 2022
Xun Huang, Arun Mallya, Ting-Chun Wang, Ming-Yu Liu
[arXiv] [Project] [Video] [Two Minute Papers]I have been fortunate to work with many talented students and interns: