Yanbei Chen

I recently joined AWS as a research scientist. I received my Ph.D. degree from the Queen Mary University of London, advised by Prof. Shaogang Gong. I obtained my M.S. degree from KTH Royal Institute of Technology and my B.S. degree from Zhejiang University. My research lies at the intersection of deep learning and computer vision. I've focused on visual learning with limited labels, with the ultimate goal to advance the use 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) to build advanced intelligent recognition models.

[Google Scholar] [Github] [Email] [LinkedIn]

Semi-Supervised and Unsupervised Deep Visual Learning: A Survey
Yanbei Chen, Massimiliano Mancini, Xiatian Zhu, Zeynep Akata
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
[PDF]

BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
Uddeshya Upadhyay, Shyamgopal Karthik, Yanbei Chen, Massimiliano Mancini, Zeynep Akata
European Conference on Computer Vision, Tel Aviv, October 2022
[PDF] [Code]

Probabilistic Compositional Embeddings for Multimodal Image Retrieval
Andrei Neculai, Yanbei Chen, Zeynep Akata.
Conference on Computer Vision and Pattern Recognition, MULA Workshop, New Orleans, USA, June 2022
[PDF] [Code]

Attention Consistency on Visual Corruptions for Single-Source Domain Generalization
Ilke Cugu, Massimiliano Mancini, Yanbei Chen, Zeynep Akata.
Conference on Computer Vision and Pattern Recognition, L3D-IVU Workshop, New Orleans, USA, June 2022
[PDF] [Code]

Robustness via Uncertainty-aware Cycle Consistency
Uddeshya Upadhyay, Yanbei Chen, Zeynep Akata.
Advances in Neural Information Processing Systems (NeurIPS), Online, December 2021
[PDF] [Poster] [Code]

Uncertainty-Guided Progressive GANs for Medical Image Translation
Uddeshya Upadhyay, Yanbei Chen, Tobias Hepp, Sergios Gatidis, Zeynep Akata.
Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Online, September 2021
[PDF] [Code]

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]

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]

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]

Conference Review Services:
• CVPR, ICCV, ECCV, NeuRIPS, ICLR, BMVC, ACCV, WACV, ICPR, ICLR, AAAI

Journal Review Services:
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• IEEE Transactions on Image Processing (TIP)
• IEEE Transactions on Cybernetics
• Neurocomputing
• Pattern Recognition

• Postdoc researcher at the Cluster of Excellence, University of Tübingen
• 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)