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Xingxing Zhang 张幸幸

A Postdoc

Education

PHD in Computer Science

2015/09 - 2020/07

BSc in Communication Engineering

2011/09 - 2015/07

Languages

  • Chinese (Native)
  • English (Professional)

Interests

About Theme

About me

I am currently a researcher in Beijing, China. Before that, I was a post-doctoral researcher in Department of Computer Science and Technology in the Tsinghua University from 2020 to 2022. I work closely with Prof. Jun Zhu. I received the Ph.D degree from the Institute of Information Science of Beijing Jiaotong University (BJTU) in 2020 (advised by Prof. Yao Zhao). I was a Visiting Student with the Department of Computer Science, University of Rochester (UR) from 2018 to 2019, working with Prof. Ji Liu.

Research Interests

Machine learning, particularly continual learning, embodied lifelong learning, data selection, zero-shot learning, and few-shot learning.

Computer vision, particularly image clustering, classification, and retrieval, motion segmentation, activity recognition, and video summarization.

Embodied Intelligence, with a particular focus on learning-based control of robotic systems, including both legged and arm-based robotics.

News

  • 2024/09 -- Our paper "PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning" is accepted by NeurIPS 2024. Congrats.
  • 2024/09 -- Our paper "Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks" is accepted by NeurIPS 2024. Congrats.
  • 2024/09 -- Our paper "To Boost Zero-shot Generalization for Embodied Reasoning with Vision-Language Pretraining" is accepted by TIP. Congrats.
  • 2023/10 -- Our paper "Towards a General Framework for Continual Learning with Pre-training" have been accepted by NeurIPS 2023 workshop.
  • 2023/09 -- Two paper have been accepted by NeurIPS 2023, one of which has been recommended as a spotlight.
  • 2023/08 -- Our wonderful work "Incorporating Neuro-inspired Adaptability for Continual Learning in Artificial Intelligence" is accepted in principle in Nature Machine Intelligence. Thank you to my closest collaborator, Dr.Liyuan Wang. We have already achieved a lot, and will continue to accomplish even more amazing work.
  • 2023/02 -- Our wonderful work "A Comprehensive Survey of Continual Learning: Theory Method and Application" is released in arXiv.
  • 2023/01 -- Our paper "ATZSL: Defensive zero-shot recognition in the presence of adversaries" is accepted by IEEE Trans. on MM.
  • 2022/12 -- It is a great honor to be invited to join CSIG Committe.
  • 2022/08 -- Our paper "Auto-Weighted Layer Representation Based View Synthesis Distortion Estimation for 3-D Video Coding" is accepted by IEEE Trans. on MM.
  • 2022/07 -- Our paper "CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One" is accepted by ECCV 2022.

Publications

Towards a General Framework for Continual Learning with Pre-training
Liyuan Wang, Jingyi Xie, Xingxing Zhang✉, Hang Su, Jun Zhu✉
NeurIPS (workshop), 2023
[PDF]
Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality
Liyuan Wang, Jingyi Xie, Xingxing Zhang✉, Mingyi Huang, Hang Su, Jun Zhu✉
NeurIPS (spotlight), 2023
[PDF]
Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation
Yilin Lyu, Liyuan Wang, Xingxing Zhang✉, Zicheng Sun, Hang Su, Jun Zhu, Liping Jing✉
NeurIPS (poster), 2023
[PDF]
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence
Liyuan Wang*, Xingxing Zhang*, Qian Li, Mingtian Zhang, Hang Su, Jun Zhu, Yi Zhong
Nature Machine Intelligence (Accepted) (NMI), 2023
[PDF]
A Comprehensive Survey of Continual Learning: Theory Method and Application
Liyuan Wang, Xingxing Zhang, Hang Su, Jun Zhu
[arxiv]
The More, The Better? Active Silencing of Non-Positive Transfer for Efficient Multi-Domain Few-Shot Classification
Xingxing Zhang, Zhizhe Liu, Weikai Yang, Liyuan Wang, Jun Zhu
ACM Multimedia (MM), 2022
[PDF]
CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One
Liyuan Wang*, Xingxing Zhang*, Qian Li, Jun Zhu, Yi Zhong
European Conference on Computer Vision (ECCV), 2022
[PDF]
Memory Replay with Data Compression for Continual Learning
Liyuan Wang*, Xingxing Zhang*, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu
The Tenth International Conference on Learning Representations (ICLR), 2022
[PDF]
机器学习中原型学习研究进展
Xingxing Zhang, Zhenfeng Zhu, Yawei Zhao, Yao Zhao
软件学报, 2021
[PDF]
Taking Modality-free Human Identification as Zero-shot Learning
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu, Shuai Zheng, Yao Zhao, Jian Cheng
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022
[PDF]
Double Low-Rank Representation With Projection Distance Penalty for Clustering
Zhiqiang Fu, Yao Zhao, Dongxia Chang, Xingxing Zhang, Yiming Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
[PDF]
Auto-weighted low-rank representation for clustering
Zhiqiang Fu, Yao Zhao, Dongxia Chang, Xingxing Zhang, Yiming Wang
[arxiv]
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries
Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu, Yao Zhao, Ji Liu
[arxiv]
Defensive Few-shot Adversarial Learning
Wenbin Li, Lei Wang, Xingxing Zhang, Jing Huo, Yang Gao, Jiebo Luo
[arxiv]
Does deep machine vision have just noticeable difference (JND)?
Jian Jin, Xingxing Zhang, Xin Fu, Huan Zhang, Weisi Lin, Jian Lou, Yao Zhao
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2021
[PDF]
Hierarchical Prototype Learning for Zero-Shot Recognition
Xingxing Zhang, Shupeng Gui, Zhenfeng Zhu, Yao Zhao, Ji Liu
IEEE Transactions on Multimedia (TMM), 2019
[PDF]
ProLFA: Representative Prototype Selection for Local Feature Aggregation
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao
Neurocomputing (NeuCom), 2019
[PDF]
Seeing All From a Few: L1-Norm-Induced Discriminative Prototype Selection
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao, Dongxia Chang, Ji Liu
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018
[PDF]
Sparsity induced prototype learning via Lp,1-norm grouping
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao
Journal of Visual Communication and Image Representation (JVCI), 2018
[PDF]
Self-Supervised Deep Low-Rank Assignment Model for Prototype Selection
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao, Deqiang Kong
International Joint Conference on Artificial Intelligence (IJCAI), 2018
[PDF]
Learning a General Assignment Model for Video Analytics
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao, Dongxia Chang
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2017
[PDF]
Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning
Shuai Zheng, Zhenfeng Zhu, Xingxing Zhang, Zhizhe Liu, Jian Cheng, Yao Zhao
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
[PDF]
To See in the Dark:  N2DGAN for Background Modeling in Nighttime Scene
Zhenfeng Zhu, Yingying Meng, Deqiang Kong, Xingxing Zhang, Yandong Guo, Yao Zhao
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020
[PDF]
Convolutional Prototype Learning for Zero-Shot Recognition
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu, Shuai Zheng, Yao Zhao, Jian Cheng
Image and Vision Computing (IVC), 2019
[PDF]
Canonical Correlation Analysis With L2,1-Norm for Multiview Data Representation
Meixiang Xu, Zhenfeng Zhu, Xingxing Zhang, Yao Zhao, Xuelong Li
IEEE Transactions on Cybernetics (TCYB), 2019
[PDF]
A Theoretical Revisit to Linear Convergence for Saddle Point Problems
Wendi Wu, Yawei Zhao, En Zhu, Xinwang Liu, Xingxing Zhang, Lailong Luo, Shixiong Wang, Jianping Yin
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2020
[PDF]
Understand Dynamic Regret with Switching Cost for Online Decision Making
Yawei Zhao, Qian Zhao, Xingxing Zhang, En Zhu, Xinwang Liu, Jianping Yin
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2019
[PDF]
Diffusion Induced Graph Representation Learning
Fuzhen Li, Zhenfeng Zhu, Xingxing Zhang, Jian Cheng, Yao Zhao
Neurocomputing (NeuCom), 2019
[PDF]
A Novel Generalized Arnold Transform-based Zero-Watermarking Scheme
Lin Sun, Jiucheng Xu, Xingxing Zhang, Wan Dong, Yun Tian
Applied Mathematics & Information Sciences (Appl Math Inf Sci), 2015
[PDF]
An Image Watermarking Scheme Using Arnold Transform and Fuzzy Smooth Support Vector Machine
Lin Sun, Jiucheng Xu, Xingxing Zhang, Yun Tian
Mathematical Problems in Engineering (MPE), 2015
[PDF]
多视角数据失补全
Xu Yang, Zhenfeng Zhu, Meixiang Xu, Xingxing Zhang
软件学报, 2018
[PDF]

Honors and Awards

  • Excellent Doctoral Dissertation of Chinese Institute of Electronics, 2020
  • Excellent Doctoral Dissertation of Beijing Jiaotong University, 2020
  • Excellent graduate in Beijing, Department of Education of Beijing, 2020
  • National Scholarship, BJTU, 2015, 2017, 2018, 2019
  • National Scholarship, HNU, 2014
  • BJTU Top Grade Scholarship - ZHIXING Scholarship (10 graduates per year), 2019
  • China Scholarship Council Scholarship, 2018
  • Excellent Undergraduate in Henan Province, 2015
  • Meritorious Award (8%), National College Mathematical Contest in Modeling, 2014
  • 2nd Prize, China Undergraduate Mathematical Contest in Modeling, 2013
  • 3rd Prize, National Computer Simulation Competition, 2014
  • 3rd Prize, National English Competition for College Students, 2014

    • Service

    Reviewer: AI, T-PAMI, ACM Computing Surveys, CVPR, ICLR, NeurIPS, etc.

    Skills

    Python & Matlab

    Pytorch & Tensorflow

    OpenCV & Scikit-learn

    Linux & MacOS

    © Xingxing Zhang 2019