Yaoyao Liu's Homepage

About Me

I am currently a third-year Ph.D. candidate in Computer Science at Max Planck Institute for Informatics, supervised by Prof. Bernt Schiele. As part of the ELLIS Ph.D. Program, I am co-supervised by Dr. Christian Rupprecht, with a planned exchange in the Visual Geometry Group (VGG) at the University of Oxford. Meanwhile, I also work closely with Prof. Andrea Vedaldi and Prof. Qianru Sun. From 2018 to 2019, I was a research intern at the National University of Singapore, working with Prof. Tat-Seng Chua and Prof. Qianru Sun. I obtained my bachelor’s degree from Tianjin University.

My research lies at the intersection of computer vision and machine learning – with a special focus on building intelligent visual systems that are continual and data-efficient. My research interests include few-shot learning, class-incremental learning, semi-supervised learning, and image generation.

I am looking for a postdoc or research scientist position in the US and EU. I would appreciate a ping if you see a job I might fit.

News

[Aug. 2022] I will serve as an area chair of AISTATS 2023.
[June 2022] I will serve as a student mentor of the CVPR Academy at CVPR 2022.
[June 2022] I will serve as a website chair of BMVC 2022.
[Sept. 2021] Our paper about class-incremental learning is accepted to NeurIPS 2021.
[Mar. 2021] Our paper about class-incremental learning is accepted to CVPR 2021.
[July 2020] Our paper about few-shot learning is accepted to ECCV 2020.
[Feb. 2020] Our paper about class-incremental learning is accepted to CVPR 2020.
[Feb. 2020] We will host the ACM Multimedia Asia 2020 conference in Singapore!
[Sept. 2019] Our paper about few-shot learning is accepted to NeurIPS 2019.
[Mar. 2019] Our paper about few-shot learning is accepted to CVPR 2019.

Publications [Google Scholar][DBLP]

TPAMI

Meta-Transfer Learning through Hard Tasks

Qianru Sun,* Yaoyao Liu,* Zhaozheng Chen, Tat-Seng Chua, Bernt Schiele (*=Equal contribution)

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Volume 44, Number 3, 2022.

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NeurIPS

RMM: Reinforced Memory Management for Class-Incremental Learning

Yaoyao Liu, Bernt Schiele, Qianru Sun

Neural Information Processing Systems (NeurIPS), 2021.

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CVPR

Adaptive Aggregation Networks for Class-Incremental Learning

Yaoyao Liu, Bernt Schiele, Qianru Sun

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

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CVIU

Learning to Teach and Learn for Semi-supervised Few-shot Image Classification

Xinzhe Li, Jianqiang Huang, Yaoyao Liu, Qin Zhou, Shibao Zheng, Bernt Schiele, Qianru Sun

Computer Vision and Image Understanding (CVIU), Volume 212, 2021.

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ECCV

An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning

Yaoyao Liu, Bernt Schiele, Qianru Sun

European Conference on Computer Vision (ECCV), 2020.

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CVPR

Mnemonics Training: Multi-Class Incremental Learning without Forgetting

Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

PDF Code Project Page BibTex Oral Presentation

NeurIPS

Learning to Self-Train for Semi-Supervised Few-Shot Classification

Xinzhe Li, Qianru Sun, Yaoyao Liu, Shibao Zheng, Qin Zhou, Tat-Seng Chua, Bernt Schiele

Neural Information Processing Systems (NeurIPS), 2019.

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CVPR

Meta-Transfer Learning for Few-Shot Learning

Qianru Sun,* Yaoyao Liu,* Tat-Seng Chua, Bernt Schiele (*=Equal contribution)

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

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600+ Citations • GitHub Stars • Featured in NUS News
Top 200 Most Cited CVPR Paper in Five Years