Huaxi Huang

Huaxi Huang

Researcher

Shanghai AI Laboratory

Biography

Dr. Huaxi Huang is currently a researcher at Shanghai AI Laboratory. He previously worked as a Computer Vision and Machine Learning Engineer at Lumachain. He also served as a CERC Research Fellow at CSIRO and the Sydney AI Centre. Dr. Huang was awarded his Ph.D. from the Faculty of Engineering and Information Technology at the University of Technology Sydney in 2022. Between 2010 and 2017, he obtained his B.Eng. and M.Eng. degrees from the School of Computer Software Engineering and the School of Computer Science and Technology at Tianjin University. His research interests include multimedia data analysis, computer vision, and trustworthy machine learning.

Interests
  • Trustworthy Machine Learning
  • Multimedia Data Analysis
  • Computer Vision
  • MLLM & LLM
Education

  • Ph.D. in Data Analytics, 2022

    University of Technology Sydney (UTS)

  • M.Eng. in Computer Science, 2017

    Tianjin University (TJU)

  • B.Eng. in Computer Software Engineering, 2014

    Tianjin University (TJU)

Recent Posts

Huaxi is now an AI Researcher at Shanghai AI Laboratory.
May 26, 2024 0 min read
Huaxi is now an AI Researcher at Shanghai AI Laboratory.
Huaxi has joined Lumachain as a Computer Vision and Machine Learning Engineer.
Dec 4, 2023 0 min read
Huaxi has joined Lumachain as a Computer Vision and Machine Learning Engineer.
Huaxi served as a Session Chair for ICME 2023.
Jul 14, 2023 0 min read
Huaxi accepted the invitation to serve as an Area Chair for MMSP 2022.
Jul 21, 2022 0 min read
Huaxi has received his Ph.D. from UTS.
Huaxi Huang
Apr 13, 2022 0 min read
Huaxi has received his Ph.D. from UTS.
See all posts

Recent Publications

Quickly discover relevant content by filtering publications.
Hui Kang, Sheng Liu, Huaxi Huang, Jun Yu, Bo Han, Dadong Wang, Tongliang Liu (2023). Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels. In arXiv 2023.

Huaxi Huang, Hui Kang, Sheng Liu, Olivier Salvado, Thierry Rakotoarivelo, Dadong Wang, Tongliang Liu (2023). PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels. In ICCV 2023.

Wenbo Xu, Huaxi Huang, Ming Cheng, Litao Yu, Qiang Wu, Jian Zhang (2023). Masked Cross-image Encoding For Few-shot Segmentation. In ICME 2023 (Oral).

Huaxi Huang, Junjie Zhang, Jian Zhang, Qiang Wu, Chang Xu (2021). PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning. In AAAI 2021 (Oral & Poster).

PDF Cite

Huaxi Huang, Junjie Zhang, Litao Yu, Jian Zhang, Qiang Wu, Chang Xu (2021). TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples. In TCSVT 2021.

Cite DOI

Huaxi Huang, Junjie Zhang, Jian Zhang, Qiang Wu (2020). Low-Rank Pairwise Alignment Bilinear Network For Few-Shot Fine-Grained Image Classification. In TMM 2020.

Cite DOI

Huaxi Huang, Junjie Zhang, Jian Zhang, Qiang Wu, Jingsong Xu (2019). Compare More Nuanced: Pairwise Alignment Bilinear Network for Few-Shot Fine-Grained Learning. In ICME 2019 (Oral).

Cite DOI

Huaxi Huang, Jingsong Xu, Jian Zhang, Qiang Wu, Christina Kirsch (2018). Railway Infrastructure Defects Recognition using Fine-grained Deep Convolutional Neural Networks. In DICTA 2018 (Oral).

Cite DOI

Huaxi Huang, Chao Hu, et al (2017). Surface defects detection for mobilephone panel workpieces based on machine vision and machine learning. In ICIA 2017 (Oral).

Cite DOI

Huaxi Huang, Changqing Zhang, Qinghua Hu, Pengfei Zhu (2016). Multi-view Representative and Informative Induced Active Learning. In PRICAI 2016 (Oral).

Cite DOI