Yunhui Guo

I am an assistant professor in the Department of Computer Science in the University of Texas at Dallas. I was a postdoc at UC Berkeley/ICSI working with Prof. Stella Yu. Previously, I completed my PhD at the University of California San Diego advised by Prof. Tajana Rosing. During my PhD, I had the pleasure to spent time at Qualcomm AI research and IBM Thomas J. Watson Research Center.



Email: yunhui.guo (at) utdallas.edu

I am looking for research interns in deep learning or computer vision. Please send me an email with your CV and transcript if you are interested.

Recent News

09/2024 Two papers were accepted by NeurIPS 2024. Congratulations to my students!

09/2024 I will be serving as an Area Chair for CVPR 2025.

07/2024 One paper about deep neural network watermarking was accepted by ECCV 2024. Congratulations to my students!

05/2024 One paper is early accepted (top 11%) by MICCAI 2024.

02/2024 Unsupervised Hyperbolic Feature Learning and Segment Every Out-of-Distribution Object are accepted by CVPR 2024.

01/2024 I will be serving as an Area Chair for ECCV 2024.

12/2023 One paper accepted in AAAI 2024.

11/2023 I was selected for the AAAI 2024 New Faculty Highlights Program.

10/2023 Two papers accepted in WACV 2024.

9/2023 Given a talk on continual learning at the 2023 AI Colloquium at DGIST.

07/2023 One paper accepted in ICCV 2023.

Research

My research is at the intersection of machine learning and computer vision. The goal of my lab is to investigate, design, and develop intelligent vision systems capable of reliable deployment in real-world scenarios. Currently, my research focuses on constructing intelligent agents that can continuously learn, dynamically adapt to evolving environments without forgetting previously acquired knowledge, and repurpose existing knowledge to adapt to novel scenarios. Our work paves the way for building intelligent and reliable systems in IoT, mobile computing, and autonomous driving, with the long-term goal of making AI more accessible and robust.

Group

Ph.D. Students

  • Ouyang Xu (Fall 2022. B.S. from Southeast University, M.S. from University of Wisconsin–Madison.)
  • Wenjie Zhao (Fall 2023. B.S. from Sichuan University, M.S. from Xi'an Jiaotong University.)
  • Sarthak Kumar Maharana (Fall 2023. B.S. from International Institute of Information Technology Bhubaneswar, M.S. from the University of Southern California.)
  • Ruiyu Mao

Master Students

Undergraduate Students

Intern

Selected Publications

STONE: A Submodular Optimization Framework for Active 3D Object Detection
Ruiyu Mao, Sarthak Kumar Maharana, Rishabh K Iyer, Yunhui Guo
NeurIPS 2024
[pdf] [code]

Continual Audio-Visual Sound Separation
Weiguo Pian, Yiyang Nan, Shijian Deng, Shentong Mo, Yunhui Guo, Yapeng Tian
NeurIPS 2024
[pdf] [code]

Not Just Change the Labels, Learn the Features: Watermarking Deep Neural Networks with Multi-View Data
Yuxuan Li, Sarthak Kumar Maharana, Yunhui Guo
ECCV 2024
[pdf] [code]

SkinCON: Towards consensus for the uncertainty of skin cancer sub-typing through distribution regularized adaptive predictive sets (DRAPS)
Zhihang Ren*, Yunqi Li*, Xinyu Li*, Xinrong Xie, Erik P. Duhaime, Kathy Fang, Tapabrata Chakraborty, Yunhui Guo, Stella X. Yu, David Whitney
MICCAI 2024
[pdf]

Unsupervised Feature Learning with Emergent Data-Driven Prototypicality
Yunhui Guo, Youren Zhang, Yubei Chen, Stella X. Yu
CVPR 2024
[pdf] [code]

Segment Every Out-of-Distribution Object
Wenjie Zhao, Jia Li, Xin Dong, Yu Xiang, Yunhui Guo
CVPR 2024
[pdf] [code]

Inconsistency-Based Data-Centric Active Open-Set Annotation
Ruiyu Mao, Ouyang Xu, Yunhui Guo
AAAI 2024
[pdf] [code]

EVOLVE: Enhancing Unsupervised Continual Learning with Multiple Experts
Xiaofan Yu, Tajana Rosing, Yunhui Guo
WACV 2024
[pdf] [code]

VEATIC: Video-based Emotion and Affect Tracking in Context Dataset
Zhihang Ren*, Jefferson Ortega*, Yifan Wang*, Zhimin Chen, Yunhui Guo, Stella X. Yu, David Whitney
WACV 2024
[pdf] [code]

Audio-Visual Class-Incremental Learning
Weiguo Pian, Shentong Mo, Yunhui Guo, Yapeng Tian
ICCV 2023
[pdf] [code]

Imbalanced Lifelong Learning with AUC Maximization
Xiangyu Zhu, Jie Hao, Yunhui Guo, Mingrui Liu
UAI 2023
[pdf] [code]

SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge
Xiaofan Yu, Yunhui Guo, Sicun Gao, Tajana Rosing
CLVision Workshop@CVPR 2023
[pdf] [code]

Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction
Yangxiao Lu, Ninad Khargonkar, Zesheng Xu, Charles Averill, Kamalesh Palanisamy, Kaiyu Hang, Yunhui Guo, Nicholas Ruozzi, Yu Xiang
RSS 2023
[pdf]

Modeling Semantic Correlation and Hierarchy for Real-world Wildlife Recognition
Dong-Jin Kim, Zhongqi Miao, Yunhui Guo, Stella X. Yu, Kyle Landolt, Mark Koneff, Travis Harrison
SPL 2023
[pdf]

Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers
Tsung-Wei Ke, Jyh-Jing Hwang, Yunhui Guo, Xudong Wang, Stella Yu
CVPR 2022

Oral presentation

[pdf] [code] [bibtex]

CO-SNE: Dimensionality Reduction and Visualization for Hyperbolic Data
Yunhui Guo, Haoran Guo, Stella Yu
CVPR 2022
[pdf] [code] [bibtex]

Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers
Yunhui Guo, Xudong Wang, Yubei Chen, Stella Yu
CVPR 2022
[pdf] [bibtex]

Improve Image-based Skin Cancer Diagnosis with Generative Self-Supervised Learning
Zhihang Ren, Yunhui Guo, Stella X. Yu, David Whitney
CHASE 2021
[pdf] [bibtex]

MAT: Processing In-Memory Acceleration for Long-Sequence Attention
Minxuan Zhou, Yunhui Guo, Weihong Xu, Bin Li, Kevin W. Eliceiri, Tajana Rosing
DAC 2021
[pdf] [bibtex]

Improved Schemes for Episodic Memory-based Lifelong Learning
Yunhui Guo*, Mingrui Liu*, Tianbao Yang, Tajana Rosing. (*equal contribution)
NeurIPS 2020

Spotlight, top 4% submissions

[pdf] [code] [bibtex]

A Broader Study of Cross-Domain Few-Shot Learning
Yunhui Guo, Noel C. Codella, Leonid Karlinsky, James V. Codella, John R. Smith, Kate Saenko, Tajana Rosing, Rogerio Feris
ECCV 2020

AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning
Yunhui Guo, Yandong Li, Liqiang Wang, Tajana Rosing
AAAI 2020
[pdf] [bibtex]

SpotTune: Transfer Learning through Adaptive Fine-tuning
Yunhui Guo, Honghui Shi, Abhishek Kumar, Kristen Grauman, Tajana Rosing, Rogério Schmidt Feris
CVPR 2019
[pdf] [code] [bibtex]

Depthwise Convolution is All You Need for Learning Multiple Visual Domains.
Yunhui Guo*, Yandong Li*, Liqiang Wang, Tajana Rosing
*Equal Contribution
AAAI 2019
[pdf] [code] [bibtex]

A Survey on Methods and Theories of Quantized Neural Networks
Yunhui Guo
[pdf] [bibtex]

Understanding Users’ Budgets for Recommendation with Hierarchical Poisson Factorization
Yunhui Guo, Congfu Xu, Hanzhang Song, Xin Wang
IJCAI 2017
[pdf] [bibtex]

Collaborative Expert Recommendation for Community-Based Question Answering
Congfu Xu, Xin Wang, Yunhui Guo
ECML/PKDD 2016
[pdf] [bibtex]

Constrained Preference Embedding for Item Recommendation
Xin Wang, CongFu Xu, Yunhui Guo, Hui Qian
IJCAI 2016
[pdf] [bibtex]

Recommendation Algorithms for Optimizing Hit Rate, User Satisfaction and Website Revenue
Xin Wang, Yunhui Guo, Congfu Xu
IJCAI 2015
[pdf] [bibtex]

Teaching

  • Instructor: UT Dallas CS 4365 Artificial Intellgence (Fall 2022, Spring 2023, Fall 2023)