Deep learning has achieved great performance in various face analysis research problems, including facial activity analysis, face super-resolution, face generation, face editing, and etc. To build an effective deep learning model, a huge amount of labeled data is indispensable. However, in real scenarios, collecting and annotating huge amounts of face images is very difficult, if not impossible. More than that, in real cases, the testing data might come from a different statistical distribution and is hard to label. All of these issues, i.e., data with limited quantities and qualities, make the learning process challenging.
Thus motivated, we organize the ACCV 2022 workshop on “Learning with Limited Data for Face Analysis” on Dec 2022, in conjunction with Asia Conferences on Computer Vision (ACCV 2022) in Macau, China. We will invite three keynote speakers to share their latest research progress in this direction at the workshop. Besides, we will invite researchers to submit their latest research output to this workshop and present them in a poster session.
Researchers are welcome to submit their work via CMT: https://cmt3.research.microsoft.com/LLDFA2022/Submission/Index
The sample topics of interest include, but are not limited to, the following:
Unsupervised, self-supervised, and semi-supervised learning in face analysis
Few-shot/zero-shot learning in face analysis
Federated learning in face analysis
Deep/transfer learning in face analysis
Face image enhancement
Face image super-resolution/reconstruction
Talking head generation
Face attribute editing
Facial activity analysis
Deepfake detection, face antispoofing
...
Paper submission deadline: 12 PM EST, Sep 20 2022
Author notification: 12 PM EST, Oct 01 2022
Camera-ready paper due: 12 PM EST, Oct 08 2022
Committee members:
Dr. Ping Liu, Scientist III, Center for Frontier AI Research, A*STAR, Singapore. Contact information: liup2 @ ihpc.a-star.edu.sg
Dr. Yuewei Lin, Computational Scientist, Brookhaven National Laboratory, NY, USA. Contact information: ywlin @ bnl.gov
Dr. Zibo Meng, Principal Research Engineer, OPPO US Research Center, CA, USA. Contact information: zibo.meng @ oppo.com
Dr. Yawei Luo, Post-Doc, Collaborative Innovation Center for Artificial Intelligence, Zhejiang University, P.R. China. Contact Information: yaweiluo329 @ gmail.com
Prof. Shangfei Wang, Professor, School of Computer Science, University of Science and Technology of China, P.R.China. Contact information: sfwang @ ustc.edu.cn
Dr. Joey Tianyi Zhou, Senior Scientist, Center for Frontier AI Research, A*STAR, Singapore, Contact information: joey_zhou @ihpc.a-star.edu.sg