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huitangtang/README.md

Hi there πŸ‘‹

πŸ‘‹ About Me

I am a Postdoc in the Department of Electronic and Computer Engineering at The Hong Kong University of Science and Technology, a member in Prof. Xiaomeng Li's Lab. I received my Ph.D. degree in the Geometric Perception and Intelligence Research Lab (Gorilla Lab) at South China University of Technology, advised by Prof. Kui Jia. Before that, I received my B.E. degree majoring in Information Engineering at South China University of Technology.

My research interests include deep learning, pattern recognition, computer vision and medical imaging. My research directions include transfer learning, domain adaptation, semi-supervised learning, etc.

I serve as a reviewer for many international top conferences and journals, e.g., CVPR, ICCV, NeurIPS, ICML, ICME, IEEE TIP, IEEE TNNLS, Pattern Recognition, Neural Networks, TMLR, etc.

Download my CV for more details.

πŸ“Ž Homepages

πŸ”₯ News

  • 2023.09: I have been a Postdoc in Dept. ECE at HKUST. πŸŽ‰
  • 2023.07: I have received my PhD degree. πŸŽ‰
  • 2023.07: My google scholar citations have exceeded 900. πŸŽ‰
  • 2023.06: I pass the PhD thesis defence and my thesis is appraised as excellent. πŸŽ‰
  • 2023.05: A new synthetic-to-real benchmark S2RDA is published by the CVF repository. πŸŽ‰
  • 2023.02: A conference paper is accepted by CVPR in 2023. πŸŽ‰
  • 2022.10: A conference paper is published by ECCV in 2022. πŸŽ‰
  • 2022.10: A journal paper is published by TPAMI in 2022. πŸŽ‰
  • 2022.06: A conference paper is published by CVPR in 2022. πŸŽ‰

Popular repositories Loading

  1. On_the_Utility_of_Synthetic_Data On_the_Utility_of_Synthetic_Data Public

    Code release for "A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain Adaptation", accepted by CVPR2023.

    Python 11 1

  2. DisClusterDA DisClusterDA Public

    Code release for Unsupervised Domain Adaptation via Distilled Discriminative Clustering published by Pattern Recognition in 2022

    Python 10 2

  3. GSF-PPF GSF-PPF Public

    Code release for ``Towards Discovering the Effectiveness of Moderately Confident Samples for Semi-Supervised Learning'' published in CVPR 2022.

    Python 8 1

  4. H-SRDC H-SRDC Public

    Code release for Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep Clustering (TPAMI 2022).

    Python 7 2

  5. STOCO STOCO Public

    Code release for ``Stochastic Consensus: Enhancing Semi-Supervised Learning with Consistency of Stochastic Classifiers'' accepted by ECCV 2022.

    Python 5 1

  6. ViCatDA ViCatDA Public

    Code release for Vicinal and categorical domain adaptation published by Pattern Recognition in 2021

    Python 3 2