Mu Cai

Hi, I am a third-year computer science Ph.D. student at University of Wisconsin-Madison, advised by Prof. Yong Jae Lee.

My research interest lies in the intersection of deep learning and computer vision. I am especially interested in visual LLM, 3D scene understanding and self-supervised learning.

Feel free to reach out if you have thoughts or ideas that align with my studies. I look forward to engaging discussions!

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NEW! Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding
Mu Cai*, Zeyi Huang*, Yuheng Li, Haohan Wang, and Yong Jae Lee
arXiv, 2023
(*equal contribution)
[arXiv] [code]

NEW! A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance
Zeyi Huang, Andy Zhou, Zijian Ling,  Mu Cai, Haohan Wang, and Yong Jae Lee
Proceedings of International Conference on Computer Vision (ICCV), 2023

Out-of-distribution Detection via Frequency-regularized Generative Models
Mu Cai, and Yixuan Li
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023 (Spotlight)
[arXiv] [code]

Masked Discrimination for Self-Supervised Learning on Point Clouds
Haotian Liu, Mu Cai, and Yong Jae Lee
Proceedings of the European Conference on Computer Vision (ECCV), 2022
[arXiv] [code] [talk]

VOS: Learning What You Don’t Know by Virtual Outlier Synthesis
Xuefeng Du, Zhaoning Wang, Mu Cai, and Yixuan Li
Proceedings of the International Conference on Learning Representations (ICLR), 2022
[arXiv] [code]

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
Mu Cai, Hong Zhang, Huijuan Huang, Qichuan Geng, Yixuan Li, and Gao Huang
In Proceedings of International Conference on Computer Vision (ICCV), 2021
[arXiv] [code]

A game-theoretic strategy-aware interaction algorithm with validation on real traffic data
Liting Sun*, Mu Cai*, Wei Zhan, and Masayoshi Tomizuka
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
(*equal contribution)

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