Workshop of Efficient Learning for Face Analysis

In the workshop titled "Efficient Learning for Face Analysis," our primary goal is to advance the field of efficient training and inference techniques for face analysis applications. These applications encompass a diverse set of tasks, including facial activity analysis, face super-resolution, face editing, face generation, talking head generation, and deepfake detection, among others. The central focus of our workshop lies in addressing the specific challenge of learning efficiency, where computational resources and access to extensive learning data are inherently constrained. Leveraging our substantial research contributions in these areas, we envision this workshop as a platform for researchers, experts, and practitioners to come together, foster meaningful discussions, showcase novel approaches, and exchange ideas. The ultimate aim is to collaboratively tackle the key issue of efficient learning for face analysis, paving the way for advancements in this important field.

Jan 08 2024 (Naupaka IV), Hawaii time

13:30-14:10: Dr. Xin Yu

14:10-14:20: Q&A

14:20-15:00: Dr. Feng Liu

15:00-15:10: Q&A

15:10-15:50: Dr. Ziwei Liu

15:50-16:00: Q&A

Researchers are welcome to submit their work in this workshop. More details will be announced soon. 

New! 

Dec-08-2023: The decision notification emails were sent out. The deadline for camera-ready version submissions is December 15, 2023.

Nov-16-2023: Due to numerous extension requests, we have opted to extend the submission deadline for the WACV 2024 workshop on "Efficient Learning for Facial Analysis" to November 30, 2023.

Nov-08-2023: Kindly proceed with the submission of your work at the following link: https://cmt3.research.microsoft.com/ELFAWACV2024/Submission/Index .

Nov-07-2023: We are delighted to announce that we have extended invitations to esteemed speakers for our organized workshop at WACV 2024: 'Efficient Learning for Facial Analysis.' Our distinguished keynote speakers include Professor Xin YU from the University of Queensland, Australia, Professor Ziwei LIU from Nanyang Technological University, Singapore, and Dr. Feng LIU from Michigan State University, USA.

Oct-28-2023: The submission process aligns with the guidelines outlined for WACV's primary conference papers, encompassing aspects like page limits and templates. Submissions will be managed through the CMT system, and it will be available online shortly.

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

• Few-shot/zero-shot learning in face attribute editing, face generation

• Federated learning in face analysis

• Deep/transfer learning in face analysis

• Deepfake detection, face antispoofing

• Model compression for face analysis

• ...

Committee members:

Dr. Ping Liu, Senior Scientist II, Center for Frontier AI Research, A*STAR, Singapore. Contact information: liu_ping @ cfar.a-star.edu.sg

Dr. Yuewei Lin, Computational Scientist, Brookhaven National Laboratory, NY, USA. Contact information: ywlin @ bnl.gov

Dr. Yang He, Scientist, Center for Frontier AI Research, A*STAR, Singapore. Contact Information: hyhy1992 @ gmail.com

Dr. Yawei Luo, Assistant Professor, Collaborative Innovation Center for Artificial Intelligence, Zhejiang University, P.R. China. Contact Information: yaweiluo329 @ gmail.com

Dr. Zibo Meng, Principal Research Engineer, OPPO US Research Center, CA, USA. Contact information: zibo.meng @ oppo.com

Prof. Idongesit Mkpong-Ruffin, Florida Agricultural & Mechanical University (FAMU), USA. Contact information: idongesit.ruffin @ famu.edu

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, Principle Scientist, Center for Frontier AI Research, A*STAR, Singapore, Contact information: joey_zhou @cfar.a-star.edu.sg