Jianzhu Guo(郭建珠)

I graduated from Southeast University with B.S. in GIS (Geographical Information System). Now, I am a Ph.D. student at National Laboratory of Pattern Recognition, Chinese Academy of Sciences, supervised by Prof. Stan Z. Li and Prof. Zhen Lei, work closely with Associate Prof. Xiangyu Zhu, where I mainly research on face & vision, including face recognition, 3D face, face anti-spoofing, face analysis and meta learning, deep learning.

Email:   guojianzhu1994@foxmail.com  |   guojianzhu1994@gmail.com

GitHub  /  CV  /  CV_EN  /  Google Scholar  /  WeChat  /  LinkedIn  /  Blog

Welcome for contacting me on things about tech & research.

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Timeline / News

  • 04 / 2021:   One paper on face recognition has been accepted by TIFS journal!
  • 03 / 2021:   Three papers submitted to KDD, ICML, ICCV 2021, respectively. Good luck to authors in CAIRI lab of WestLake University!
  • 12 / 2020:   One paper on face recognition has been accepted by AAAI 2021, congrats to Xiaqing Xu.
  • 09 / 2020:   Code release for 3DDFA_V2 GitHub stars (ECCV2020).
  • 07 / 2020:   Two papers on 3D face have been accepted by ECCV 2020.
  • 03 / 2020:   Two papers (one oral) on face recognition have been accepted by CVPR 2020.
  • 07 / 2019:   One paper on face anti-spoofing has been accepted by AVSS 2019.
  • 03 / 2019:   One paper (oral) on face anti-spoofing has been accepted by ICB 2019.
  • 06 / 2018:   Code release for 3DDFA GitHub stars (TPAMI2017).
  • 04 / 2018:   One paper on 3D face & face recognition has been accepted by CCBR 2018, with a dataset MeGlass released.
  • 04 / 2018:   One paper on micro-emotion recognition has been accepted by IEEE Access.
  • 03 / 2017:   One paper on micro-emotion recognition has been accepted by FG 2017.
  • 03 / 2017:   The winner of FG2017 facial micro-expression recognition competition, acknowledgement to my collaborator Shuai Zhou. Code released at EmotionChallenge.
  • 03 / 2017:   The silver medal (rank5) of HUAWEI Code Craft 2017 in Beijing site, acknowledgement to my partners Yudong Wu and Xingyuan Gao.



Publications

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Decomposed Meta Batch Normalization for Fast Domain Adaptation in Face Recognition


Jianzhu Guo, Xiangyu Zhu, Zhen Lei, Stan Z. Li
TIFS (IEEE Transactions on Information Forensics and Security) (Accepted)
paper /

This paper proposes a novel training remedy by decomposing the model into the weight parameters and the BN statistics in the training phase. Based on decomposing, we design a novel framework via meta-learning, called Decomposed Meta Batch Normalization (DMBN) for fast domain adaptation in face recognition.

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Searching for Alignment in Face Recognition


Xiaqing Xu, Qiang Meng, Yunxiao Qin, Jianzhu Guo, Chenxu Zhao, Feng Zhou, Zhen Lei
AAAI 2021
arxiv / paper / poster /

This paper proposes an efficient method Face Alignment Policy Search (FAPS) to search the optimal alignment template in face recognition. A well-designed benchmark is also proposed to evaluate the searched policy.

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Towards Fast, Accurate and Stable 3D Dense Face Alignment


Jianzhu Guo, Xiangyu Zhu, Yang Yang, Zhen Lei, Yang Fan, Stan Z. Li
ECCV 2020
arxiv / paper / supp / video1 / video2 / code /

We propose a novel regression framework, named 3DDFA_V2, to make a balance among speed, accuracy and stability. Our model runs at over 50fps on a single CPU core (>200fps with ONNX acceleration) and outperforms other state-of-the-art heavy models simultaneously. Code and models are available at https://github.com/cleardusk/3DDFA_V2.

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Beyond 3DMM Space: Towards Fine-grained 3D Face Reconstruction


Xiangyu Zhu, Fan Yang, Di Huang, Chang Yu, Hao Wang, Jianzhu Guo, Zhen Lei, Stan Z. Li
ECCV 2020
paper / supp / code /

This paper constructs a new dataset Fine-Grained 3D face (FG3D) with 200k samples for training, and proposes a Fine-Grained reconstruction Network (FGNet) concentrating on shape modi cation by warping the network input and output to the UV space. FG3D is available at https://github.com/XiangyuZhu-open/Beyond3DMM.

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Learning Meta Face Recognition in Unseen Domains


Jianzhu Guo, Xiangyu Zhu, Chenxu Zhao, Dong Cao, Zhen Lei, Stan Z. Li
CVPR 2020 (Oral Presentation, acceptance rate 5%)
arxiv / paper / code /

We propose a novel face recognition method via meta-learning named Meta Face Recognition (MFR) to learn a generalized model performing well on unseen domains. Besides, we propose two benchmarks for generalized face recognition evaluation. The proposed benchmarks will be available at https://github.com/cleardusk/MFR.

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Domain Balancing: Face Recognition on Long-Tailed Domains


Dong Cao, Xiangyu Zhu, Xingyu Huang, Jianzhu Guo, Zhen Lei
CVPR 2020
arxiv / paper /

This paper proposes a Domain Frequency Instructor (DFI), a light weighted Residual Balancing Mapping (RBM) block and a Domain Balancing Margin (DBM) to improve generalization on tailed domains.

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Improving Face Anti-Spoofing by 3D Virtual Synthesis


Jianzhu Guo, Xiangyu Zhu, Jinchuan Xiao, Zhen Lei, Genxun Wan, Stan Z. Li
International Conference On Biometrics, ICB 2019 (Oral Presentation, acceptance rate 11.2%)
arxiv / paper /

We present a method to synthesize virtual spoof data in 3D space to improve face anti-spoofing. The synthetic virtual samples can significantly boost the anti-spoofing performance when combined with a proposed data balancing strategy.

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Face Synthesis for Eyeglass-Robust Face Recognition


Jianzhu Guo, Xiangyu Zhu, Zhen Lei, Stan Z. Li
CCF Chinese Conference on Biometric Recognition (CCBR), Urumqi, China, Aug. 11-12, 2018
arxiv / paper / code /

In the application of face recognition, eyeglasses could significantly degrade the recognition accuracy. In this paper, we propose to address this problem in a virtual synthesis manner.

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Dominant and Complementary Emotion Recognition From Still Images of Faces


Jianzhu Guo, Zhen Lei, Jun Wan, et al.
IEEE Access, 6(1), 26391-26403, 2018
paper / code /

External journal version.

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Multi-modality Network with Visual and Geometrical Information for Micro Emotion Recognition


Jianzhu Guo, Shuai Zhou, Jinlin Wu, Jun Wan, Xiangyu Zhu, Zhen Lei, Stan Z. Li
FG, Washington, DC. May 30 –June 3, 2017
paper / code /

Winner of face micro-emotion competition held on FG 2017.

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3DMA: A Multi-modality 3D Mask Face Anti-spoofing Database


Jinchuan Xiao, Yinhang Tang, Jianzhu Guo, Yang Yang, Xiangyu Zhu, Zhen Lei, Stan Z. Li
16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2019
paper /

We release a multi-modality 3D mask face anti-spoofing database named 3DMA, which contains 920 videos of 67 genuine subjects wearing 48 kinds of 3D masks, captured in visual (VIS) and near-infrared (NIR) modalities.




Under Review

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AutoMix: Unveiling the Power of Mixup


Zicheng Liu, Siyuan Li, Di Wu, Zhiyuan Chen, Lirong Wu, Jianzhu Guo, Stan Z. Li
Under Review (ICCV 2021), 2021
arxiv / paper /

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OT-Cleaner: Refurbishing Unclean Labels with Optimal Transport


Jun Xia, Cheng Tan, Jianzhu Guo, Lirong Wu, Yongjie Xu, Stan Z. Li
Under Review (ICML 2021), 2021

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Deep Manifold Attributed Graph Embedding with Graph Geodesic Similarity


Zelin Zang, Siyuan Li, Di Wu, Jianzhu Guo, Yongjie Xu, Stan Z. Li
Under Review (KDD 2021), 2021




Competitions

  • 1-st Winner of Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head, in conjunction with FG 2017, First author. [Code]

  • HUAWEI Code Craft 2017: Awarded Silver Medal (rank 5th) in Beijing Site. Team with three members, equal contribution.



Projects (Public)

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3DDFA_V2: Fast, accurate and stable 3D dense face alignment   [Star history]
GitHub stars GitHub forks Closed Issues Open Issues

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3DDFA: Real-time 3D face reconstruction   [Star history]
GitHub stars GitHub forks Closed Issues Open Issues

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MeGlass: An eyeglass face dataset collected and cleaned for face recognition evaluation
GitHub stars GitHub forks

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Learning Meta Face Recognition in Unseen Domains
GitHub stars GitHub forks

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ImageToAscii: Python tools for Image Ascii Art
GitHub stars

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Source code for 1st winner of face micro-emotion competition held on FG 2017
GitHub stars

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UCAS utils to ease your campus life!
GitHub stars




Video demos

Hathaway




Service

  • Program Committee Member of AAAI 2021.
  • Program Committee Member of ACM MM 2020, 2021.
  • Reviewer for CVPR, ICCV, ECCV, AAAI, MM, IJCAI, IJCB, BMVC, FG, Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Transactions on Image Processing (TIP), Transactions on Cybernetics (T-C), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), TBIOM, Knowledge-Based Systems, IEEE Access, Neurocomputing, IET Computer Vision, etc.



Contact (WeChat QR Code)

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Wow, this guy's website is awesome