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Yuxiong WANG Assistant Professor Department of Computer Science, University of Illinois at Urbana-Champaign Email: yxw[at]illinois[dot]edu |
-- Albert Einstein |
Welcome to my homepage. I am an Assistant Professor in the Department of Computer Science at University of Illinois at Urbana-Champaign (UIUC). Before joining Illinois CS, I was a postdoctoral fellow in the Robotics Institute at Carnegie Mellon University, advised by Prof. Martial Hebert. I was a visitor in the Center for Data Science at New York University, working with Prof. Jean Ponce. I obtained my Ph.D. under the supervision of Prof. Martial Hebert in the Robotics Institute. I have also been closely working with Prof. Deva Ramanan and Prof. Ruslan Salakhutdinov. I recently received the Best Paper Honorable Mention Award for streaming perception in ECCV 2020.
My research lies in computer vision, machine learning, and robotics, with a specific focus on meta-learning, few-shot learning, predictive learning, and streaming perception.
I am looking for self-motivated Ph.D. / MS students starting Fall 2022. Please feel free to contact me if interested.
Our group also has openings for interns during Spring / Summer 2022. Please feel free to contact me if interested.
3D Human Motion Prediction and Its Application in Human-Robot Interaction
Learning to Predict Diverse Futures from a Single Past Motion Sequence
Yuxiong Wang*, Liang-Yan Gui*, José M. F. Moura
Under review, 2019 (* indicates equal contribution). [Preprint]
Teaching Robots to Predict Human Motion
Liang-Yan Gui, Kevin Zhang, Yuxiong Wang, Xiaodan Liang, José M. F. Moura, Manuela M. Veloso
Oral Presentation, IROS, 2018. [PDF]
Few-Shot Human Motion Prediction via Meta-Learning
Liang-Yan Gui, Yuxiong Wang, Deva Ramanan, José M. F. Moura
ECCV, 2018. [PDF]
Compositional Learning
Learning Compositional Representations for Few-Shot Recognition
Pavel Tokmakov, Yuxiong Wang, Martial Hebert
Under review, 2019. [PDF]
Knowledge Distillation and Learning to Learn in Model Space
Few-Shot Human Motion Prediction via Meta-Learning
Liang-Yan Gui, Yuxiong Wang, Deva Ramanan, José M. F. Moura
ECCV, 2018. [PDF]
Learning to Model the Tail
Yuxiong Wang, Deva Ramanan, Martial Hebert
NeurIPS, 2017. [PDF]
Also in [Contributed Talk, NeurIPS Workshop on Meta-Learning], 2017.
Learning to Learn: Model Regression Networks for Easy Small Sample Learning
Yuxiong Wang, Martial Hebert
ECCV, 2016. [PDF]
Rethinking Fine-Tuning via Developmental Learning
Growing a Brain: Fine-Tuning by Increasing Model Capacity
Yuxiong Wang, Deva Ramanan, Martial Hebert
CVPR, 2017. [PDF] [Invited Talk, CVPR Workshop on Continuous and Open-Set Learning], 2017.
Factorized Convolutional Networks: Unsupervised Fine-Tuning for Image Clustering
Liang-Yan Gui, Liangke Gui, Yuxiong Wang, Louis-Philippe Morency, José M. F. Moura
Oral Presentation, WACV, 2018. [PDF]
Unsupervised Meta-Learning
Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs
Yuxiong Wang, Martial Hebert
NeurIPS, 2016. [PDF]
Few-Shot Hash Learning for Image Retrieval
Yuxiong Wang, Liangke Gui, Martial Hebert
ICCV Workshops, 2017. [PDF]
Discovering Unsupervised Binary Codes for Learning from Small Sample Sets
Yuxiong Wang, Martial Hebert
CVPR BigVision Workshop, 2016.
Learning by Transferring from Unsupervised Universal Sources
Yuxiong Wang, Martial Hebert
Oral Presentation, AAAI, 2016. [PDF]
Non-Negative Matrix and Tensor Factorization and Its Applications
Non-Negative Matrix Factorization: A Comprehensive Review
Yuxiong Wang, Yu-Jin Zhang
IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 6, pp.1336-1353, 2013. [PDF]
Image Inpainting via Weighted Sparse Non-Negative Matrix Factorization
Yuxiong Wang, Yu-Jin Zhang
ICIP, 2011. [PDF]
Neighborhood Preserving Non-Negative Tensor Factorization for Image Representation
Yuxiong Wang, Liangyan Gui, Yu-Jin Zhang
Oral Presentation, ICASSP, 2012. [PDF]
Non-Negative Matrix Factorization for Image Representation
Yuxiong Wang
Best Master’s Thesis, Tsinghua University, May 2012.
Sparse Representation and Dictionary Learning for Image Classification
Self-Explanatory Sparse Representation for Image Classification
Yuxiong Wang*, Baodi Liu*, Bin Shen, Yu-Jin Zhang, Martial Hebert
Learning Dictionary on Manifolds for Image Classification
Bao-Di Liu, Yuxiong Wang, Yu-Jin Zhang, Bin Shen
Pattern Recognition, vol. 46, no. 7, pp. 1879-1890, 2013. [PDF]
Blockwise Coordinate Descent Schemes for Sparse Representation
Bao-Di Liu, Yuxiong Wang, Bin Shen, Yu-Jin Zhang, Yanjiang Wang
ICASSP, 2014. [PDF]
Discriminant Sparse Coding for Image Classification
Baodi Liu, Yuxiong Wang, Yu-Jin Zhang, Yin Zheng
ICASSP, 2012. [PDF]