Welcome to Yuqian Fu’s homepage

Biography

I am currectly a postdoc researcher at INSAIT, Sofia, Bulgaria, working with Prof. Luc Van Gool and Dr. Danda Paudel. Previously, I was a postdoc researcher at Computer Vision Lab (CVL), ETH Zürich, Switzerland, where I was also fortunate to be mentored by Prof. Luc Van Gool.

I received my Ph.D. degree from School of Computer Science, Fudan University, China, in June 2023, advised by Prof. Yu-Gang Jiang and co-advised by Prof. Yanwei Fu. During my Ph.D studies, I also worked closely with Associate Professor Jingjing Chen. Before that, I received my bachelor’s degree in computer science from Zhejiang University of Technology, China, in June 2018, supervised by Associate Professor Cong Bai.

My research topics are computer vision and deep learning. I mainly focus on few-shot learning and cross domain issues, especially cross-domain few-shot learning, and few-shot video action recognition during my Ph.D period. Currently, I am also exploring multimodal approaches e.g., grounding and multi-sensor fusion.

Recently, I have several open positions for visiting/master/PhD in INSAIT especially for multimodal related tasks. If you are interested in joining or remotely working with us, feel free to drop an email to me: yuqian.fu@insait.ai.

News

  • [04/2024] I joined INSAIT as a postdoc researcher.
  • [12/2023] One paper is accepted by AAAI2024.
  • [09/2023] I joined CVL lab at ETH Zürich.
  • [07/2023] One paper is accepted by ACM MM 2023.
  • [06/2023] I have earned a doctoral degree.
  • [04/2023] I have received 100 citations!
  • [02/2023] One paper is accepted by CVPR2023.
  • [10/2022] One paper is accepted by TIP.
  • [06/2022] Two papers are accepted by ACM MM 2022.
  • [12/2021] I am recognized as an outstanding student of Fudan University.
  • [06/2021] One paper is accepted by ACM MM 2021.
  • [04/2021] One paper is accepted by ICMR 2021.
  • [07/2020] One paper is accepted by ACM MM 2020.
  • [12/2019] I am awarded the Chinese National Scholarship.
  • [07/2019] One paper is accepted by ACM MM 2019.
  • [09/2018] I joined FVL lab at Fudan University.

Selected Publications

StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning
Yuqian Fu, Yu Xie, Yanwei Fu, Yu-Gang Jiang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
[Paper][Code][Youtube Video][Bilibili Video][Project Page]
Generalized Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Data
Yuqian Fu, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang
IEEE Transactions on Image Processinig (TIP), 2022.
[Paper]
ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning
Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2022.
[Paper][Code][Youtube Video][Bilibili Video]
TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning
Linhai Zhuo, Yuqian Fu, Jingjing Chen, Yixin Cao, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2022.
[Paper]
Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot Learning
Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang
arXiv preprint, 2022.
[Paper][Code]
Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target Data
Yuqian Fu, Yanwei Fu, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2021.
[Paper][Code][Youtube Video][Bilibili Video][Project Page]
Can Action be Imitated? Learn to Reconstruct and Transfer Human Dynamics from Videos
Yuqian Fu, Yanwei Fu, Yu-Gang Jiang
International Conference on Multimedia Retrieval (ICMR). 2021. (Oral)
[Paper][Bilibili Video]
Depth Guided Adaptive Meta-Fusion Network for Few-shot Video Recognition
Yuqian Fu, Li Zhang, Junke Wang, Yanwei Fu, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2020. (Oral)
[Paper][Code][Youtube Video][Bilibili Video][Project Page]
Embodied One-Shot Video Recognition: Learning from Actions of a Virtual Embodied Agent
Yuqian Fu, Chengrong Wang, Yanwei Fu, Yu-Xiong Wang, Cong Bai, Xiangyang Xue, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2019. (Oral)
[Paper][Code][UnrealAction Dataset]