Ze Wang

Ze Wang


Contact: wang5026 [at] purdue.edu

I am currently a postdoc at the Purdue University Electrical and Computer Engineering department, working with Prof. Qiang Qiu.

My Ph.D. research focuses on computer vision models that efficiently learn and adapt with minimal supervision. Motivated by this objective, my research has progressed in three main directions: (1) vision model adaptation in low-rank filter subspace; (2) few-shot adaptive vision models; and (3) representation learning with generative models. For more details, please refer to my research statement.

Before joining Purdue University in 2020, I was a Ph.D. student in Electrical and Computer Engineering at Duke University, advised by Prof. Qiang Qiu and Prof. Guillermo Sapiro.

I got my B.E. from Beihang University in 2017.

Recent Publications

- 2023

  • Binary Latent Diffusion
    Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu
    CVPR, 2023
    [pdf] [code]

  • Energy-Inspired Self-Supervised Pretraining for Vision Models
    Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu
    ICLR Notable-top-25%, 2023
    [pdf]

  • Meta-OLE: Meta-learned Orthogonal Low-Rank Embedding
    Ze Wang, Yue Lu, Qiang Qiu
    WACV, 2023
    [pdf]

- 2022

  • Few-Shot Fast-Adaptive Anomaly Detection
    Ze Wang, Yipin Zhou, Rui Wang, Tsung-Yu Lin, Ashish Shah, Ser-Nam Lim
    NeurIPS, 2022

  • Energy-Inspired Self-Supervised Pretraining for Vision Models
    Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu
    ICML Pre-training Workshop, 2022
    [pdf]

  • Continual Learning with Filter Atom Swapping
    Zichen Miao, Ze Wang, Wei Chen, Qiang Qi
    ICLR Spotlight, 2022
    [pdf]

- 2021

  • Image Generation using Continuous Filter Atoms
    Ze Wang, Seunghyun Hwang, Zichen Miao, Qiang Qiu
    NeurIPS Spotlight, 2021
    [pdf]

  • Learning to Learn Dense Gaussian Processes for Few-Shot Learning
    Ze Wang, Zichen Miao, Xiantong Zhen, Qiang Qiu
    NeurIPS, 2021
    [pdf]

  • Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks
    Zichen Miao, Ze Wang, Xiantong Zhen, Qiang Qiu
    NeurIPS, 2021
    [pdf]

  • Adaptive Convolutions with Per-pixel Dynamic Filter Atom
    Ze Wang, Zichen Miao, Jun Hu, Qiang Qiu
    ICCV, 2021
    [pdf] [code]

  • Cirrus: A Long-range Bi-pattern LiDAR Dataset
    Ze Wang, Sihao Ding, Ying Li, Jonas Fenn, Sohini Roychowdhury, Andreas Wallin, Lane Martin, Scott Ryvola, Guillermo Sapiro, Qiang Qiu
    ICRA, 2021
    [pdf] [dataset]

  • Using Text to Teach Image Retrieval
    Haoyu Dong, Ze Wang, Qiang Qiu, Guillermo Sapiro
    CVPR Multimodal Learning and Applications Workshop, 2021
    [pdf]

- 2020

  • A Dictionary Approach to Domain-Invariant Learning in Deep Networks
    Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
    NeurIPS, 2020
    [pdf]

  • Stochastic Conditional Generative Networks with Basis Decomposition
    Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
    ICLR, 2020
    [pdf]

- 2019

  • Range Adaptation for 3D Object Detection in LiDAR
    Ze Wang, Ding, Ying Li, Minming Zhao, Sohini Roychowdhury, Andreas Wallin, Guillermo Sapiro, Qiang Qiu
    ICCV Workshop on Autonomous Driving Best Paper Award, 2019
    [pdf]

  • The structure transfer machine theory and applications
    Baochang Zhang, Wankou Yang, Ze Wang, Lian Zhuo, Jungong Han, Xiantong Zhen
    IEEE Transactions on Image Processing, 2019
    [pdf]

  • Understanding Urban Dynamics via Context-aware Tensor Factorization with Neighboring Regularization
    Jingyuan Wang, Junjie Wu, Ze Wang, Fei Gao, Zhang Xiong
    IEEE Transactions on Knowledge and Data Engineering, 2019
    [pdf]

For earier publications please refer to my Google Scholar.