Yanbei Chen



I am currently a postdoctoral researcher within the Cluster of Excellence Machine Learning at the University of Tübingen in Germany, working with Prof. Zeynep Akata at the Explainable Machine Learning group. I obtained my PhD from Queen Mary University of London in the UK, advised by Prof. Shaogang Gong. Prior to that, I received my master's degree from KTH Royal Institute of Technology in Stockholm, Sweden, supervised by Prof. Atsuto Maki, and my bachelor's degree from Zhejiang University in Hangzhou, China.

My research interests lie at the intersection of deep learning and computer vision. I've focused on developing semi-supervised, unsupervised, and cross-domain deep learning algorithms and techniques for visual learning, with the ultimate goal to advance the automatic exploitation of large-scale visual data using minimal human supervision. I am also dedicated to designing multimodal learning algorithms that could connect, correlate, and integrate multiple data modalities (e.g. vision, language, audio) in an explainable way to build intelligent perception systems.

[Google Scholar] [Email] [Github]



Publications

Area I: Multimodal Learning

Distilling Audio-Visual Knowledge by Compositional Contrastive Learning
Yanbei Chen, Yongqin Xian, Sophia Koepke, Ying Shan, Zeynep Akata.
Conference on Computer Vision and Pattern Recognition, Online, June 2021
[PDF] [Supplementary] [Poster] [Code]



Image Search with Text Feedback by Visiolinguistic Attention Learning
Yanbei Chen, Shaogang Gong, Loris Bazzani.
Conference on Computer Vision and Pattern Recognition, Seattle, USA, June 2020
[PDF] [Supplementary] [Poster] [Code] (featured in [Amazon Science Blog] and [deeplearning.ai])



Learning Joint Visual Semantic Matching Embeddings for Language-Guided Retrieval
Yanbei Chen, Loris Bazzani.
European Conference on Computer Vision, Online, August 2020
[PDF]



Area II: Visual Learning in Limited-Label Regime

Semi-Supervised Learning under Class Distribution Mismatch
Yanbei Chen, Xiatian Zhu, Wei Li, Shaogang Gong.
Association for the Advancement of Artificial Intelligence, New York City, USA, February 2020
[PDF] [Supplementary] [Poster] [Code]



Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
Yanbei Chen, Xiatian Zhu, Shaogang Gong.
International Conference on Computer Vision, Seoul, Korea, October 2019
[PDF] [Supplementary] [Poster]



Deep Association Learning for Unsupervised Video Person Re-identification
Yanbei Chen, Xiatian Zhu, Shaogang Gong.
British Machine Vision Conference, Newcastle, UK, September 2018
[PDF] [Poster] [Code]



Semi-supervised Deep Learning with Memory
Yanbei Chen, Xiatian Zhu, Shaogang Gong.
European Conference on Computer Vision, Munich, Germany, September 2018
[PDF] [Poster] [Code]



Area III: Person Re-Identification

Person Re-Identification by Deep Learning Multi-Scale Representations
Yanbei Chen, Xiatian Zhu, Shaogang Gong.
International Conference on Computer Vision, Workshop on Cross-Domain Human Identification, Venice, Italy, October 2017
[PDF]


Academic Services
    Conference Reviewers:
  • CVPR2020/2021, ICCV2021, NeuRIPS2020/2021, BMVC2020/2019, ACCV2020, WACV2021, ICPR2021

  • Journal Reviewers:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Image Processing (TIP)
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
  • IEEE Transactions on Cybernetics
  • Neurocomputing
  • Pattern Recognition
Experiences
  • Research Intern at Tencent in 2020 Summer
  • Research Intern at Amazon Berlin in 2019 Summer
  • Teaching Assistant in QMUL, 2019 Spring: Deep Learning and Computer Vision (ECS795P)
  • Teaching Assistant in QMUL, 2018 Spring: Deep Learning and Computer Vision (ECS795P)