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. Zhen Lei and Prof. Stan Z. Li, 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: jianzhu.guo@nlpr.ia.ac.cn or guojianzhu1994@foxmail.com
GitHub /
CV /
CV_EN /
Google Scholar /
WeChat /
LinkedIn /
Blog
Looking for a full-time job.
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1 paper on face recognition has been accepted by AAAI 2021, congrats to Xiaqing Xu.
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Code release for 3DDFA_V2
(ECCV2020).
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2 papers on 3D face have been accepted by ECCV 2020.
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2 papers (1 oral) on face recognition have been accepted by CVPR 2020.
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1 paper (oral) on face anti-spoofing has been accepted by ICB 2019.
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Code release for 3DDFA
(TPAMI2017).
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1 paper on face anti-spoofing has been accepted by AVSS 2019, congrats to Jinchuan Xiao.
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1 paper on 3D face & face recognition has been accepted by CCBR 2018, with the MeGlass dataset released.
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2 papers on micro-emotion recognition have been accepted by Access 2018 and FG 2017.
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The winner of FG2017 facial micro-expression recognition competition, acknowledgement to my collaborator Shuai Zhou. Code released at EmotionChallenge.
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The silver medal (rank5) of HUAWEI Code Craft 2017 in Beijing site, acknowledgement to my partners Yudong Wu and Xingyuan Gao.
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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
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The alignment step in face recognition has attracted little attention. We firstly explore and highlight the effects of different alignment templates on face recognition. Then, for the first time, we try to search for the optimal template automatically. We construct a well-defined searching space by decomposing the template searching into the crop size and vertical shift, and propose an efficient method Face Alignment Policy Search (FAPS).
Besides, a well-designed benchmark is proposed to evaluate the searched policy and experiments on our proposed benchmark validate the effectiveness of our method to improve face recognition performance.
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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
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video1 /
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We propose a novel regression framework which makes a balance among speed, accuracy and stability. Firstly, on the basis of a lightweight backbone, we propose a meta-joint optimization strategy
to dynamically regress a small set of 3DMM parameters, which greatly enhances speed and accuracy simultaneously. To further improve the stability on videos, we present a virtual synthesis method to transform one still image to a short-video incorporating in-plane and out-of-plane face moving. Our model runs at over 50fps on a single CPU core and outperforms other state-of-the-art heavy models simultaneously. Code and models will be 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
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We propose a solution to construct large-scale fine-grained 3D data from RGB-D images, and construct a new dataset Fine-Grained 3D face (FG3D) with 200k samples for training. We also propose a Fine-Grained reconstruction Network (FGNet) concentrating on shape modication by warping the network input and output to the UV space. The proposed method and code will be 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%)
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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
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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 /
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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 (CCBR2018), Urumqi, China, Aug. 11-12, 2018
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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
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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
FG2017, Washington, DC. May 30 –June 3, 2017
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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
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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.
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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
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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 (Major Revision, 2 AQ & 1 RQ), 2020
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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]
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HUAWEI Code Craft 2017: Awarded Silver Medal (rank 5th) in Beijing Site. Team with three members, equal contribution.
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Program Committee Member of AAAI 2021.
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Program Committee Member of ACM MM 2020.
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Reviewer for CVPR, ICCV, ECCV, AAAI, MM, IJCAI, IJCB, BMVC, FG, Transactions on Pattern Analysis and Machine Intelligence, Cybernetics, Knowledge-Based Systems, Neurocomputing, etc.
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Contact (WeChat QR Code)
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