Xun Huang Profile Photo

Xun Huang

Senior Research Scientist
Adobe Research
Pittsburgh, PA

Email: xuhuang at adobe dot com

Google Scholar | GitHub | Papers | Collaborators

My name is Xun Huang (pronounced as /shuun hwang/). I am a Senior Research Scientist at Adobe, working on multimodal Generative AI. Prior to joining Adobe, I was a researcher at NVIDIA working on the Picasso and Edify. I obtained my PhD from the Department of Computer Science at Cornell University, advised by Professor Serge Belongie. During PhD, my research was supported by Adobe Research Fellowship (2019), Snap Research Fellowship (2019), and NVIDIA Graduate Fellowship (2018).

My research interests include:

Publications

Paper 1

JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation

CVPR, 2024

Yu Zeng, Vishal M Patel, Haochen Wang, Xun Huang, Ting-Chun Wang, Ming-Yu Liu, Yogesh Balaji

[arXiv] [Project]
Paper 2

DiffCollage: Parallel Generation of Large Content with Diffusion Models

CVPR, 2023

Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu

[arXiv] [Project]
Magic3D

Magic3D: High-Resolution Text-to-3D Content Creation

CVPR 2023

Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin

[arXiv] [Project]
eDiff-I

eDiff-I: Text-to-Image Diffusion Models with Ensemble of Expert Denoisers

arXiv 2022

Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, Tero Karras, Ming-Yu Liu

[arXiv] [Project] [Video]
PoE-GANs

Multimodal Conditional Image Synthesis with Product-of-Experts GANs

ECCV 2022

Xun Huang, Arun Mallya, Ting-Chun Wang, Ming-Yu Liu

[arXiv] [Project] [Video]
GAN Survey

Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications

Proceedings of the IEEE 2021

Xun Huang, Arun Mallya, Ting-Chun Wang, Ming-Yu Liu

[arXiv]
PointFlow

PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows

ICCV 2019 (Oral)

Guandao Yang*, Xun Huang*, Zekun Hao, Ming-Yu Liu, Serge Belongie, Bharath Hariharan (*equal contribution)

[arXiv] [Code] [Video]
FUNIT

Few-shot Unsupervised Image-to-Image Translation

ICCV 2019

Ming-Yu Liu, Xun Huang, Arun Mallya, Tero Karras, Timo Aila, Jaakko Lehtinen, Jan Kautz

[arXiv] [Code] [Video]
MUNIT

Multimodal Unsupervised Image-to-Image Translation

ECCV 2018

Xun Huang, Ming-Yu Liu, Serge Belongie, Jan Kautz

[arXiv] [Code] [Video]
Image Captioning

Learning to Evaluate Image Captioning

CVPR 2018

Yin Cui, Guandao Yang, Andreas Veit, Xun Huang, Serge Belongie

[arXiv] [Code]
Controllable Video Generation

Controllable Video Generation with Sparse Trajectories

CVPR 2018

Zekun Hao, Xun Huang, Serge Belongie

[PDF] [Code]
AdaIN

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

ICCV 2017 (Oral)

Xun Huang, Serge Belongie

[arXiv] [Code]
SGAN

Stacked Generative Adversarial Networks

CVPR 2017

Xun Huang, Yixuan Li, Omid Poursaeed, John Hopcroft, Serge Belongie

[arXiv] [Code]
Convolutional Pseudoprior

Top-Down Learning for Structured Labeling with Convolutional Pseudoprior

ECCV 2016

Saining Xie*, Xun Huang*, Zhuowen Tu (*equal contribution)

[arXiv]
SALICON

SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks

ICCV 2015

Xun Huang, Chengyao Shen, Xavier Boix, Qi Zhao

[PDF]

Student mentees/interns

I have been fortunate to work with many talented students and interns:

Teaching