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Weijian Deng

Third-year PhD Student

About Me

I am a third-year PhD student at the College of Engineering and Computer Science, Australian National University, where I am supervised by Prof. Stephen Gould and Dr. Liang Zheng. I work closely with Dr. Yumin Suh. Before that, I received the M.Phil in Computer Science from the University of the Chinese Academy of Sciences in 2019, advised by Prof. Qixiang Ye and Prof. Jianbin Jiao. I obtained the B.Eng. from Beijing Jiaotong University in 2016, advised by Dr. Jupeng Li.

Research interest My general research interest is to develop deep learning models for computer vision tasks (e.g., fine-grained object recognition). Recently, I focus on Understanding Model Decision under Dynamic Testing Environments. Please check our [ CVPR 2021 work] and [ ICML 2021 work].

[Curriculum Vitae; Google Scholar]

News

  • [Dec 2021] One paper on model decision understanding is accepted to IEEE TPAMI. [Project]
  • [May 2021] One paper is accepted to ICML, 2021. [Paper, Project]
  • [Mar 2021] One paper is accepted to CVPR, 2021. [Paper, Project]
  • [Jul 2020 - Sep 2020] Summer intern in NEC Labs America. Wonderful experience with my talented mentors Yumin Suh, Xiang Yu, Masoud Faraki, and Manmohan Chandraker.
  • [Aug 2020] VisDA-2020 challenge successfully ends. Congratulations to the [final teams]!
    • Big thanks to all committee members Kate Saenko, Liang Zheng, and Xingchao Peng!
  • [Jan 2020] One paper is accepted to IEEE TCSVT. [Paper]
  • [Jul 2020] Honoured to be recognized by ECCV2020 as a top reviewer. [Link]
  • [Jul 2019] Study PhD program at The Australian National University. My reseach is supported by Australian Governmen Scholarship [AGRTP].
  • [Jun 2019] Receive M.Eng. from the University of the Chinese Academy of Sciences.
  • [Jun 2019] Win 3rd place out of 84 participants in vehicle re-identification in CVPR 2019 AI-City Challenge.
    • [Paper, Code]
  • [Jul 2018 - Nov 2018] Reserch assistant in Singapore University of Technology and Design (SUTD).
  • [Mar 2018] One paper is accepted to CVPR, 2018. [Paper, Code]
  • [Jul 2017] One paper is accepted to ICCV, 2017. [Paper, Code]

Publications

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AutoEval: Are Labels Always Necessary for Classifier Accuracy Evaluation?

Weijian Deng and Liang Zheng

IEEE TPAMI [Project, Paper]

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What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?

Weijian Deng, Stephen Gould, and Liang Zheng

ICML, 2021. [Paper, BibTex, Project, Slides, Poster]

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Are Labels Always Necessary for Classifier Accuracy Evaluation?

Weijian Deng and Liang Zheng

CVPR, 2021. [Paper, Project, BibTex, Poster, Slides]

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Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

Weijian Deng, Liang Zheng, et al.

CVPR, 2018. [Paper, Code, BibTex, Poster]

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Rethinking Triplet Loss for Domain Adaptation

Weijian Deng, Liang Zheng, Yifan Sun, Jianbin Jiao

IEEE TCSVT, 2020. [Paper, BibTex]

(Journal version of "Domain alignment with triplets")

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SVDNet for Pedestrian Retrieval

Yifan Sun, Liang Zheng, Weijian Deng, Shengjin Wang

ICCV, 2017. [Paper, Code, BibTex, Poster]

More on Google Scholar

Selected Projects

Similarity-preserving Image-image Domain Adaptation for Person Re-identification

Weijian Deng, Liang Zheng, Qixiang Ye, Yi Yang, Jianbin Jiao (arXiv 2018) [Paper, Code]

Fine-grained Classification via Categorical Memory Networks

Weijian Deng, Joshua Marsh, Stephen Gould, Liang Zheng (arXiv 2020) [Paper]

Visual Domain Adaptation Challenge (VisDA 2020 in conjunction with ECCV 2020)

This year we focus on domain adaptive instance retrieval, where the source and target domains have completely different classes (instance IDs). The particular task is to retrieve the pedestrian instances of the same ID as the query image. [Chanllenge Page]

Organizers: Kate Saenko (Boston University), Liang Zheng (Australian National University), Xingchao Peng (Boston University), Weijian Deng (Australian National University)

The Third Place in Vehicle Re-identification in CVPR 2019 AI-City Challenge

Win 3rd place out of 84 participants [Paper, Code]

Work Experience

Research Intern NEC Laboratories America, Inc. (NEC Labs) (2020-06 - 2020-10)

Mentors: Yumin Suh, Xiang Yu, Masoud Faraki, and Manmohan Chandraker

  • Research of Multi-task Learning

Research Assistant Singapore University of Technology and Design (2018-07 - 2018-11)

Mentor: Dr. Liang Zheng

  • Research of Domain Adaptation

Research Student University of Chinese Academy of Sciences, PriSDL (2016-01 - 2019-07)

Advised by Prof. Jianbin Jiao

  • Research of Object Recognition and Detection