Update: The workshop programme times are now confirmed.
It should be noted that Authors need to register with their respective paper IDs so that registration
will be linked with the correct paper. Congratulations to all accepted papers and we look forward
to meeting you at the conference.
Paper ID: W14-01
Face Detection by Aggregating Visible Components
Jiali Duan, Shengcai Liao, Stan Li.
Paper ID: W14-02
Deep Architectures for Face Attributes
Tobias Baumgartne, Jack Culpepper.
Paper ID: W14-03
Automatic Micro-expression Recognition from Long Video using a Single Spotted Apex
Sze Teng Liong, John See, KokSheik Wong, Raphael Chung-Wei Phan.
Paper ID: W14-04
Failure Detection for Facial Landmark Detectors
Andreas Steger, Radu Timofte, Luc Van Gool.
Paper ID: W14-05
Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences
Anil Bas, William Smith, Timo Bolkart, Stefanie Wuhrer.
Paper ID: W14-06
Multiple Facial Attributes Estimation based on Weighted Heterogeneous Learning
Takayoshi Yamashita, Hiroshi Fukui, Ryo Matsui, Yuu Kato, Yuji Yamauchi, Hironobu Fujiyoshi.
Paper ID: W14-07
Reliable Age Estimation Based On Apt Gabor Features Selection and SVM
ArulMurugan Ambikapathi, Yi-Tseng Cheng, Gee-Sern Hsu.
Paper ID: W14-08
VFSC: A Very Fast Sparse Clustering to Cluster Faces from Videos
Dinh-Luan Nguyen, Minh-Triet Tran.
Paper ID: W14-09
Deep or Shallow Facial Descriptors? A Case for Facial Attribute Classification and Face Retrieval
Rasoul Banaeeyan, Haris Lye, Mohammad Faizal Ahmad Fauzi, Hezerul Abdul Karim, John See.
Paper ID: W14-10
A Hierarchical Framework for Face Recognition Robust to Makeup Changes
Zhenzhu Zheng.
Paper ID: W14-11
A Main Directional Maximal Difference Analysis for Spotting Micro-expressions
Su-Jing Wang, Shuhang Wu, Xiaolan Fu.
Paper ID: W14-12
Aesthetic Evaluation of Facial Portraits Using Compositional Augmentation for Deep CNNs
Magzhan Kairanbay, John See, Lai-Kuan Wong.
Call for Papers:
A face tells about one's gender, age, emotion, ethnicity, attractiveness and much more. It has long
been considered as a vital biometric trait. Tremendous research works are being carried out in the
fields of computer vision and psychology. As deep learning is considered an unconventional approach
that reveals visual intelligence close to humans, it is of great interest to gather works on facial
informatics from different disciplines using conventional/unconventional methods, and to stimulate
communications across these disciplines.
This workshop aims to promote interactions between researchers, scholars, practitioners, engineers
and students from across industry and academia on all aspects of facial informatics. It will include
both oral and poster presentations. We are soliciting original works that address a wide range of
issues including, but not limited to:
- Face detection, tracking and/or recognition
- Face alignment
- Facial trait analysis
- Facial attributes recognition (for example, expression, age, gender, ethnicity, attractiveness)
- Video-based facial analysis and understanding
- Micro-facial expressions
- Deep learning on face
- Face databases
- Protocols and evaluations
In addition, manuscripts with preliminary results are also welcome.
