Yuxiong Wang

Yuxiong WANG



Assistant Professor

Department of Computer Science, University of Illinois at Urbana-Champaign

Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign

Faculty Fellow, National Center for Supercomputing Applications (NCSA)

Email: yxw[at]illinois[dot]edu

Google Scholar


Make things as simple as possible, but not simpler

-- 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 receive the Best Paper Honorable Mention Award for streaming perception in ECCV 2020, and Best Paper Award Finalist in CVPR 2019, 2022. I am recognized as a Notable Area Chair in ICLR 2023, and an Expert Reviewer in TMLR.

My research lies in computer vision, machine learning, and robotics, with a specific focus on open-world AI, meta-learning, few-shot learning, predictive learning, and streaming perception.

I am looking for self-motivated Ph.D. / MS students starting Fall 2023. Please feel free to contact me if interested.

Our group also has openings for interns during Spring / Summer 2023. Please feel free to contact me if interested.

Current Research Topics

  • Meta-learning and learning to learn
  • Open-world, multi-modal, few/low-shot, and self-supervised learning
  • 3D vision
  • Generative modeling, predictive learning
  • Human motion prediction for human-robot interaction
  • Reinforcement learning, robot skill learning
  • In-the-wild applications in robotics, autonomous driving, agriculture, materials science, chemistry, healthcare, etc.

Group

  • PhD
    • Shengcao Cao
    • Junkun Chen
    • Eric Lee
    • Xiang Li
    • Yunze Man
    • Ziqi Pang
    • Michal Shlapentokh-Rothman
    • Kai Yan
    • Yuanyi Zhong
  • MS
  • Undergraduate

Dissertation

Selected Publications

2024

    Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

    Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang

    Arxiv, 2024. [PDF] [Website]


    Aligning Large Multimodal Models with Factually Augmented RLHF

    Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liangyan Gui, Yu-Xiong Wang, Yiming Yang, Kurt Keutzer, Trevor Darrell

    Arxiv, 2024. [PDF] [Website]


    Instruct 4D-to-4D: Editing 4D Scenes as Pseudo-3D Scenes Using 2D Diffusion

    Linzhan Mou, Jun-Kun Chen, Yu-Xiong Wang

    CVPR, 2024. [PDF] [Website]


    ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editing

    Jun-Kun Chen, Samuel Rota Bulò, Norman Müller, Lorenzo Porzi, Peter Kontschieder, Yu-Xiong Wang

    CVPR, 2024. [PDF] [Website]


    TAMM: TriAdapter Multi-Modal Learning for 3D Shape Understanding

    Zhihao Zhang, Shengcao Cao, Yu-Xiong Wang

    CVPR, 2024. [PDF] [Website]


    Situational Awareness Matters in 3D Vision Language Reasoning

    Yunze Man, Liangyan Gui, Yu-Xiong Wang

    CVPR, 2024. [PDF] [Website]


    Restricted Memory Banks Improve Video Object Segmentation: A Revisit

    Junbao Zhou, Ziqi Pang, Yu-Xiong Wang

    CVPR, 2024. [PDF] [Website]


    Region-Based Representations Revisited

    Michal Shlapentokh-Rothman, Ansel Blume, Yao Xiao, Yuqun Wu, Sethuraman T V, Heyi Tao, Jae Yong Lee, Wilfredo Torres, Yu-Xiong Wang, Derek Hoiem

    CVPR, 2024. [PDF] [Website]


    Frozen Transformers in Language Models Are Effective Visual Encoder Layers

    Ziqi Pang, Ziyang Xie*, Yunze Man*, Yu-Xiong Wang

    Spotlight Oral Presentation, ICLR, 2024. [PDF] [Website]


    SOHES: Self-supervised Open-world Hierarchical Entity Segmentation

    Shengcao Cao, Jiuxiang Gu, Jason Kuen, Hao Tan, Ruiyi Zhang, Handong Zhao, Ani Nenkova, Liangyan Gui, Tong Sun, Yu-Xiong Wang

    ICLR, 2024. [PDF] [Website]


    Robust Model-Based Optimization for Challenging Fitness Landscapes

    Saba Ghaffari, Ehsan Saleh, Alex Schwing, Yu-Xiong Wang, Martin D. Burke, Saurabh Sinha

    ICLR, 2024. [PDF] [Website]

2023

    YouTubePD: A Multimodal Benchmark for Parkinson’s Disease Analysis

    Andy Zhou*, Samuel Li*, Pranav Sriram*, Xiang Li*, Jiahua Dong*, Ansh Sharma, Yuanyi Zhong, Shirui Luo, Maria Jaromin, Volodymyr Kindratenko, George Heintz, Christopher Zallek, Yu-Xiong Wang

    NeurIPS Datasets and Benchmarks Track, 2023. [PDF] [Website]


    ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields

    Jiahua Dong, Yu-Xiong Wang

    NeurIPS, 2023. [PDF] [Website]


    HASSOD: Hierarchical Adaptive Self-Supervised Object Detection

    Shengcao Cao, Dhiraj Joshi, Liang-Yan Gui, Yu-Xiong Wang

    NeurIPS, 2023. [PDF] [Website]


    A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories

    Kai Yan, Alexander G. Schwing, Yu-Xiong Wang

    NeurIPS, 2023. [PDF] [Website]


    Generating and Distilling Discrete Adversarial Examples from Large-Scale Models

    Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang

    NeurIPS, 2023. [PDF] [Website]


    Contrastive Learning Relies More on Spatial Inductive Bias Than Supervised Learning: An Empirical Study

    Yuanyi Zhong*, Haoran Tang*, Junkun Chen*, Yu-Xiong Wang

    ICCV, 2023. [PDF] [Website]


    MV-Map: Offboard HD-Map Generation with Multi-view Consistency

    Ziyang Xie*, Ziqi Pang*, Yu-Xiong Wang

    ICCV, 2023. [PDF] [Website]


    Improving Equivariance in State-of-the-Art Supervised Depth and Normal Predictors

    Yuanyi Zhong, Anand Bhattad, Yu-Xiong Wang, David A. Forsyth

    ICCV, 2023. [PDF] [Website]


    Video State-Changing Object Segmentation

    Jiangwei Yu*, Xiang Li*, Xinran Zhao, Hongming Zhang, Yu-Xiong Wang

    ICCV, 2023. [PDF] [Website]


    Multi-task View Synthesis with Neural Radiance Fields

    Shuhong Zheng, Zhipeng Bao, Martial Hebert, Yu-Xiong Wang

    ICCV, 2023. [PDF] [Website]


    InterDiff: Forecasting 3D Human-Object Interaction with Physics-Informed Diffusion

    Sirui Xu, Zhengyuan Li, Yu-Xiong Wang, Liangyan Gui

    ICCV, 2023. [PDF] [Website]


    Revisiting Deformable Convolution for Depth Completion

    Revisiting Deformable Convolution for Depth Completion

    Xinglong Sun, Jean Ponce, Yu-Xiong Wang

    IROS, 2023. [PDF] [Website]


    Streaming Motion Forecasting for Autonomous Driving

    Streaming Motion Forecasting for Autonomous Driving

    Ziqi Pang, Deva Ramanan, Mengtian Li, Yu-Xiong Wang

    IROS, 2023. [PDF] [Website]


    DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception

    DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception

    Yunze Man, Liangyan Gui, Yu-Xiong Wang

    IROS, 2023. [PDF] [Website]


    Learning Lightweight Object Detectors via Progressive Knowledge Distillation

    Learning Lightweight Object Detectors via Progressive Knowledge Distillation

    Shengcao Cao, Mengtian Li, James Hays, Deva Ramanan, Yu-Xiong Wang, Liangyan Gui

    ICML, 2023. [PDF] [Website]


    NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds

    NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds

    Jun-Kun Chen, Jipeng Lyu, Yu-Xiong Wang

    CVPR, 2023. [PDF] [Website]


    Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking

    Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking

    Ziqi Pang, Jie Li, Pavel Tokmakov, Dian Chen, Sergey Zagoruyko, Yu-Xiong Wang

    CVPR, 2023. [PDF] [Code]


    Contrastive Mean Teacher for Domain Adaptive Object Detectors

    Contrastive Mean Teacher for Domain Adaptive Object Detectors

    Shengcao Cao, Dhiraj Joshi, Liangyan Gui, Yu-Xiong Wang

    CVPR, 2023. [PDF] [Code]


    BEV-Guided Multi-Modality Fusion for Driving Perception

    BEV-Guided Multi-Modality Fusion for Driving Perception

    Yunze Man, Liangyan Gui, Yu-Xiong Wang

    CVPR, 2023. [PDF] [Website]


    Object Discovery from Motion-Guided Tokens

    Object Discovery from Motion-Guided Tokens

    Zhipeng Bao, Pavel Tokmakov, Yu-Xiong Wang, Adrien Gaidon, Martial Hebert

    CVPR, 2023. [PDF][Website] [Code]


    GAPS: Few-Shot Incremental Semantic Segmentation via Guided Copy-Paste Synthesis

    GAPS: Few-Shot Incremental Semantic Segmentation via Guided Copy-Paste Synthesis

    Ri-Zhao Qiu, Peiyi Chen, Wangzhe Sun, Yu-Xiong Wang, Kris Hauser

    CVPR Workshop on Learning with Limited Labelled Data, 2023. [PDF] [Website]


    From N to N+1: Learning to Detect Novel Animals with SAM in the Wild

    From N to N+1: Learning to Detect Novel Animals with SAM in the Wild

    Garvita Allabadi, Ana Lucic, Yu-Xiong Wang, Vikram Adve

    CVPR Workshop on CV4Animals, 2023. [PDF] [Website]


    Stochastic Multi-Person 3D Motion Forecasting

    Stochastic Multi-Person 3D Motion Forecasting

    Sirui Xu, Yu-Xiong Wang*, Liangyan Gui*

    ICLR, Notable-Top-25%, 2023. [PDF] [Website]


    Do Pre-Trained Models Benefit Equally in Continual Learning?

    Do Pre-Trained Models Benefit Equally in Continual Learning?

    Kuan-Ying Lee, Yuanyi Zhong, Yu-Xiong Wang

    WACV, 2023. [PDF] [Code]


    Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields

    Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields

    Mingtong Zhang*, Shuhong Zheng*, Zhipeng Bao, Martial Hebert, Yu-Xiong Wang

    WACV, 2023. [PDF] [Code]

2022

    CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations

    CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations

    Kai Yan, Alexander G. Schwing, Yu-Xiong Wang

    NeurIPS, 2022. [PDF] [Website]


    LECO: Learning with an Evolving Class Ontology

    LECO: Learning with an Evolving Class Ontology

    Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong

    NeurIPS, 2022. [PDF] [Website]


    The Curse of Zero Task Diversity: On the Failure of Transfer Learning to Outperform MAML and their Empirical Equivalence

    The Curse of Zero Task Diversity: On the Failure of Transfer Learning to Outperform MAML and their Empirical Equivalence

    Brando Miranda, Patrick Yu, Yu-Xiong Wang, Oluwasanmi Koyejo

    NeurIPS Workshop on Meta-Learning, Contributed Talk, 2022. [PDF] [Poster]


    Towards Overcoming Data Scarcity in Materials Science: Unifying Models and Datasets with a Mixture of Experts Framework

    Towards Overcoming Data Scarcity in Materials Science: Unifying Models and Datasets with a Mixture of Experts Framework

    Rees Chang, Yu-Xiong Wang, Elif Ertekin

    Nature npj Computational Materials, 2022. [PDF] [Code]


    Generalized Few-Shot Node Classification on Graphs

    Generalized Few-Shot Node Classification on Graphs

    Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong

    ICDM, 2022. [PDF]


    Diverse Human Motion Prediction Guided by Multi-Level Spatial Temporal Anchors

    Diverse Human Motion Prediction Guided by Multi-Level Spatial Temporal Anchors

    Sirui Xu, Yu-Xiong Wang*, Liang-Yan Gui*

    ECCV, 2022. [PDF] [Website]


    PointTree: Transformation Robust Point Cloud Encoder with Relaxed K-D Trees

    PointTree: Transformation Robust Point Cloud Encoder with Relaxed K-D Trees

    Junkun Chen, Yu-Xiong Wang

    ECCV, 2022. [PDF] [Code]


    Generative Modeling for Multi-Task Visual Learning

    Generative Modeling for Multi-Task Visual Learning

    Zhipeng Bao, Martial Hebert, Yu-Xiong Wang

    ICML, 2022. [PDF] [Code]


    Is Self-Supervised Contrastive Learning More Robust Than Supervised Learning?

    Is Self-Supervised Contrastive Learning More Robust Than Supervised Learning?

    Yuanyi Zhong, Haoran Tang, Junkun Chen, Jian Peng, Yu-Xiong Wang

    ICML Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward, 2022. [PDF]


    DIVeR: Real-time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Rendering

    DIVeR: Real-time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Rendering

    Liwen Wu, Jae Yong Lee, Anand Bhattad, Yu-Xiong Wang, David Forsyth

    CVPR, Best Paper Award Finalist, 2022. [PDF] [Website]


    Discovering Objects that Can Move

    Discovering Objects that Can Move

    Zhipeng Bao, Pavel Tokmakov, Allan Jabri, Yu-Xiong Wang, Adrien Gaidon, Martial Hebert

    CVPR, 2022. [PDF] [Website]


    Long-Tailed Recognition via Weight Balancing

    Long-Tailed Recognition via Weight Balancing

    Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan, Shu Kong

    CVPR, 2022. [PDF] [Code]


    Embracing Single Stride 3D Object Detector with Sparse Transformer

    Embracing Single Stride 3D Object Detector with Sparse Transformer

    Lue Fan, Ziqi Pang, Tianyuan Zhang, Yu-Xiong Wang, Hang Zhao, Feng Wang, Naiyan Wang, Zhaoxiang Zhang

    CVPR, 2022. [PDF] [Code]


    On the Importance of Firth Bias Reduction in Few-Shot Classification

    On the Importance of Firth Bias Reduction in Few-Shot Classification

    Saba Ghaffari*, Ehsan Saleh*, David Forsyth, Yu-Xiong Wang

    ICLR, 2022. [PDF] [Website]

2021

    SIRfyN: Single Image Relighting from your Neighbors

    SIRfyN: Single Image Relighting from your Neighbors

    David Forsyth, Anand Bhattad, Pranav Asthana, Yuanyi Zhong, Yu-Xiong Wang

    Arxiv, 2021. [PDF]


    Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation

    Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation

    Yuanyi Zhong, Bodi Yuan, Hong Wu, Zhiqiang Yuan, Jian Peng, Yuxiong Wang

    ICCV, 2021. [PDF]


    Learning to Hallucinate Examples from Extrinsic and Intrinsic Supervision

    Learning to Hallucinate Examples from Extrinsic and Intrinsic Supervision

    Liangke Gui*, Adrien Bardes*, Ruslan Salakhutdinov, Alexander Hauptmann, Martial Hebert, Yuxiong Wang

    ICCV, 2021 (* indicates equal contribution). [PDF]


    On the Importance of Distractors for Few-Shot Learning

    On the Importance of Distractors for Few-Shot Learning

    Rajshekhar Das, Yuxiong Wang, José M. F. Moura

    ICCV, 2021. [PDF]


    Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection

    Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection

    Nadine Chang, Zhiding Yu, Yuxiong Wang, Anima Anandkumar, Sanja Fidler, Jose M. Alvarez

    ICML, 2021. [PDF]


    Hallucination Improves Few-Shot Object Detection

    Hallucination Improves Few-Shot Object Detection

    Weilin Zhang, Yuxiong Wang

    CVPR, 2021. [PDF]


    DAP: Detection-Aware Pre-training with Weak Supervision

    DAP: Detection-Aware Pre-training with Weak Supervision

    Yuanyi Zhong, Jianfeng Wang, Lijuan Wang, Jian Peng, Yuxiong Wang, , Lei Zhang

    CVPR, 2021. [PDF]


    Unlocking the Full Potential of Small Data with Diverse Supervision

    Unlocking the Full Potential of Small Data with Diverse Supervision

    Ziqi Pang, Zhiyuan Hu, Pavel Tokmakov, Yuxiong Wang, Martial Hebert

    CVPR Workshop on Learning from Limited or Imperfect Data, 2021. [PDF]


    Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis

    Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis

    Zhipeng Bao, Yuxiong Wang, Martial Hebert

    ICLR, 2021. [PDF]

2020

    Towards Streaming Perception

    Towards Streaming Perception

    Mengtian Li, Yuxiong Wang, Deva Ramanan

    Oral Presentation, Best Paper Honorable Mention, ECCV, 2020. [PDF] [Project]


    Alpha Net:
Adaptation with Composition in Classifier Space

    Alpha Net: Adaptation with Composition in Classifier Space

    Nadine Chang, Jayanth Koushik, Michael J. Tarr, Martial Hebert, Yuxiong Wang

    Under review, 2020. [Preprint]


    Progressive Knowledge Distillation for Few-Shot Learning

    Few-shot GAN

    Few-Shot Generative Adversarial Networks

    Chunyan Bai, Yan Xu, Boyu Liu, Ruslan Salakhutdinov, Martial Hebert, Yuxiong Wang

    Under review, 2020. [Preprint]


    Prototypical Adaptation for Few-Shot Classification

    Prototypical Adaptation for Few-Shot Classification

    Rajshekhar Das, Yuxiong Wang, José M. F. Moura

    Under review, 2020. [Preprint]


    Learning Generalizable Representations via Diverse Supervision

    Learning Generalizable Representations via Diverse Supervision

    Ziqi Pang, Zhiyuan Hu, Pavel Tokmakov, Yuxiong Wang, Martial Hebert

    Under review, 2020. [arXiv]


    Stochastic Dual-Attention Long-Term Motion Prediction

    Learning to Predict Diverse Futures from a Single Past Motion Sequence

    Yuxiong Wang*, Liang-Yan Gui*, José M. F. Moura

    Under review, 2020. [Preprint]


    Meta-Learning by Hallucinating Useful Examples

    Meta-Learning by Hallucinating Useful Examples

    Yuxiong Wang*, Yuki Uchiyama*, Martial Hebert, Karteek Alahari

    Under review, 2020. [Preprint]

2019

    Meta-Learning to Detect Rare Objects

    Meta-Learning to Detect Rare Objects

    Yuxiong Wang, Deva Ramanan, Martial Hebert,

    ICCV, 2019. [PDF][Poster]


    Compositional Learning

    Learning Compositional Representations for Few-Shot Recognition

    Pavel Tokmakov, Yuxiong Wang, Martial Hebert

    ICCV, 2019. [PDF][Poster]


    Image Deformation Meta-Networks for One-Shot Learning

    Image Deformation Meta-Networks for One-Shot Learning

    Zitian Chen, Yanwei Fu, Yuxiong Wang, Lin Ma, Wei Liu, Martial Hebert

    Oral Presentation, Best Paper Award Finalist, CVPR, 2019. [PDF][Poster][Talk]


    Embodied One-Shot Video Recognition: Learning from Actions of a Virtual Embodied Agent

    Embodied One-Shot Video Recognition: Learning from Actions of a Virtual Embodied Agent

    Yuqian Fu, Chengrong Wang, Yanwei Fu, Yuxiong Wang, Cong Bai, Xiangyang Xue, Yu-Gang

    Jiang, Lin Ma, Wei Liu, Martial Hebert

    ACM MM, 2019. [PDF]

2018

    Motion Prediction for Human-Robot Interaction

    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 Motion Prediction via Meta-Learning

    Few-Shot Human Motion Prediction via Meta-Learning

    Liang-Yan Gui, Yuxiong Wang, Deva Ramanan, José M. F. Moura

    ECCV, 2018. [PDF][Poster]


    Human-Like Motion Prediction

    Adversarial Geometry-Aware Human Motion Prediction

    Yuxiong Wang*, Liang-Yan Gui*, Xiaodan Liang, José M. F. Moura

    Oral Presentation, ECCV, 2018 (* indicates equal contribution). [PDF][Poster][Talk]


    Task-Oriented Generative Modeling

    Low-Shot Learning from Imaginary Data

    Yuxiong Wang, Ross Girshick, Martial Hebert, Bharath Hariharan

    Spotlight Oral Presentation, CVPR, 2018. [PDF][Poster][Talk]


    Unsupervised Fine-Tuning

    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]

2017

    Meta-Learning of Model Dynamics for Long-Tail Recognition

    Unsupervised Binary Codes

    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. [Poster]


    Continual Learning and Fine-Tuning by Increasing Model Capacity

2016

    Improving CNN Transferability through Large-Scale Unsupervised Meta-Training

    Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs

    Yuxiong Wang, Martial Hebert

    NeurIPS, 2016. [PDF][Poster]


    Learning to Learn through Model Regression Networks

    Learning to Learn: Model Regression Networks for Easy Small Sample Learning

    Yuxiong Wang, Martial Hebert

    ECCV, 2016. [PDF][Poster]


    Transfer Learning from Unsupervised Universal Sources

    Learning by Transferring from Unsupervised Universal Sources

    Yuxiong Wang, Martial Hebert

    Oral Presentation, AAAI, 2016. [PDF]

2015

    Transfer Learning from Unsupervised Universal Sources

    Model Recommendation: Generating Object Detectors from Few Samples

    Yuxiong Wang, Martial Hebert

    CVPR, 2015. [PDF][Poster][Project]


2014

    Self-Explanatory Sparse Representation for Image Classification

    Self-Explanatory Sparse Representation for Image Classification

    Yuxiong Wang*, Baodi Liu*, Bin Shen, Yu-Jin Zhang, Martial Hebert

    ECCV, 2014 (* indicates equal contribution). [PDF][Poster]


    Blockwise Coordinate Descent Schemes for Sparse Representation

    Bao-Di Liu, Yuxiong Wang, Bin Shen, Yu-Jin Zhang, Yanjiang Wang

    ICASSP, 2014. [PDF]

2013

    Non-Negative Matrix Factorization: A Comprehensive Review

    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]


    Learning Dictionary on Manifolds for Image Classification

    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]

2012

    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.


    Discriminant Sparse Coding for Image Classification

    Baodi Liu, Yuxiong Wang, Yu-Jin Zhang, Yin Zheng

    ICASS, 2012. [PDF]

2011

    Non-negative Matrix Factorization: A Comprehensive Review

    Image Inpainting via Weighted Sparse Non-Negative Matrix Factorization

    Yuxiong Wang, Yu-Jin Zhang

    ICIP, 2011. [PDF][Poster]