Call for Participants

The aim of the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018) Doctoral Consortium is to provide a forum for PhD students to discuss their research and career objectives with the international research community. FG 2018 Doctoral Consortium aims to provide a networking environment that will enable the doctoral students to establish new contacts and collaborations with other researchers and to equip the new generation of bright researchers with career options in academia and industry.

The Doctoral Consortium will be a half-day event, starting with a catered lunch combined with an informal introduction by senior researchers and followed by discussions with attendees. Attendance will be by invitation only. During oral sessions, the accepted student participants will present their research and will receive feedback from the invited committee. The students will also present their work during a poster session in the main conference, to receive feedback from the rest of the community.

Eligible students are invited to apply for the Doctoral Consortium. Successful applicants are expected to actively participate in the whole program, whereas their co-authors are expected to attend the Doctoral Consortium and the main conference poster session.

ELIGIBILITY

We encourage submissions from PhD students who are already working on their dissertations with some results already published or close to publication. We encourage diversity and equality, both in terms of research topics as well as participating institutions and individuals. We do not expect more than two students to be invited from each institution to represent a diverse sample. Women are especially encouraged to apply. It is not necessary to have a paper appearing in FG 2018 in order to apply to participate.

SUBMISSION

To apply for the Doctoral Consortium, please submit:
- A CV (max 1 page).
- An extended abstract (max 4 pages) following the FG 2018 paper format. It should describe the research vision of the applicant, a brief summary of the work till date, a working plan, and a discussion of future plans and challenges. The work should still be in progress.
- A supporting letter from the thesis advisor that endorses the student's application to this Doctoral Consortium and briefly describes the progress or status of the student's thesis work.

All materials should be combined into a single PDF file and submitted through the FG 2018 DC submission system .

REVIEW AND SELECTION PROCESS

All submissions will be peer-reviewed by TPC members. Paper topics should be related to the conference topics. Submissions will be evaluated on:
- Quality of the submission.
- Expected benefits for the student's research.
- Student's contribution to the diversity of topics, backgrounds, methodology, etc.

FINANCIAL SUPPORT

Students selected for participation in the Doctoral Consortium may be considered to receive financial support for travel, lodging and registration expenses, which is contingent upon available funds.

IMPORTANT DATES

Submission deadline: March 14, 2018
Notification of acceptance: March 21, 2018
Doctoral consortium date: TBA, 2018

CONTACT

For further questions, contact the Doctoral Consortium Chairs:
 Yan Tong (tongy@cec.sc.edu)
Shangfei Wang (sfwang@ustc.edu.cn )
Ronald Poppe (r.w.poppe@uu.nl)

Accepted Doctoral Students:

1. Personalized Face and Gesture Analysis using Hierarchical Bayesian Neural Networks, Ajjen Joshi (Boston U.)
2. Machine learning for human learning, Han Jiang (Worcester Polytechnic Institute)
3. Visual Recognition of Families in the Wild, Joseph P Robinson (Northeastern U.)
4. Multi-Modal Depression Detection and Estimation, Le Yang (Northwestern Polytechnical U.)
5. Multimodal Emotion Analysis with Application in Human Computer Interaction, Umur Aybars Ciftci (Binghamton U.)
6. Robust and Accurate Eye Gaze Tracking and Its Applications, Kang Wang (Rensselaer Polytechnic Institute)
7. Robust Remote Heart Rate Estimation using rPPG Signals: from Hand-craft to Learning-based Features, Xuesong Niu (ICT, Chinese Academy of Sciences)
8. Learning discriminative features for facial expression recognition, Jie Cai (U. of South Carolina)
9. Spontaneous Facial Expression Analysis in Videos, Ruijing Yang (Northwest U.)
10. Using Facial Features to Contextualize Linguistic Analysis in Multimodal Communication, Md Kamrul Hasan (U. of Rochester)
11. Spatio-temporal Features in Videos for Emotion Recognition in the Wild, Garima Sharma (Indian Institute of Technology)
12. On Face Segmentation, Face Swapping, and Face Perception, Yuval Nirkin (The Open U. of Israel)
13. Unsupervised Binary Representation Learning for Visual Recognition, Yueqi Duan (Tsinghua U.)
14. From 3D Face Alignment to Pose-invariant Face Recognition, Jiankang Deng (Imperial College London)
15. 3D Face Modeling: Images, Shapes, and Biology, Feng Liu (Sichuan U.)

Reviewers and Mentors:

Tadas Baltrusaitis, Carnegie Mellon University
Kevin Bailly, ISIR
Liming Chen, Ecole Centrale de Lyon
Abhinav Dhall, Indian Institute of Technology Ropar
Hamdi Dibeklioglu, Bilkent University
Anna Esposito, Seconda Universita di Napoli
Yun Raymond Fu, Northeastern University
Julian Fierrez, Universidad Autonoma de Madrid
Zakia Hammal, University of Pittsburgh
Hu Han, ICT, Chinese Academy of Sciences
Ehsan Hoque, University of Rochester
Xiaohua Huang, University of Oulu
Huibin Li, Xian Jiaotong University
Xiaoming Liu, Michigan State University
Marwa Mahmoud, University of Cambridge
Daniel McDuff, Microsoft
Costanza Navarretta, University of Copenhagen
Ronald Poppe, University of Twente
Linlin Shen, Shenzhen University
Yan Tong, University of South Carolina
ShangFei Wang, USTC
Jacob Whitehill, Worcester Polytechnic Institute
Qijun Zhao, Sichuan University