Call for papers RFIAP

RFIAP is an interdisciplinary gathering of researchers at the intersection of pattern recognition, image, perception, and machine learning applied to these topics.


This year, RFIAP will be held jointly with CAp (Conférence sur l'Apprentissage automatique) 2020. Sessions on topics of common interest for the two communities will be organized.


Below is a summary of the important dates and the main novelties of these editions:

RFIAP will be held jointly with CAp;
RFIAP will take place from the 23th to the 26th of June 2020;
The submission deadline for RFIAP is the 19th of February 2020;
Papers accepted in international conferences can be submitted for oral presentation;
The authors will have the possibility to write a rebuttal to the reviews.


We encourage the submission of full research papers (6-8 pages) as well as short papers (2 pages). The short papers track provides an opportunity for sharing valuable early-stage work or results of pluridisciplinary work and encourage discussions. Submitted papers can be either in French or in English if the first author is a non-native French speaker.


We also encourage the submission of recent papers accepted to high level conferences and journals in pattern recognition. Papers should be submitted with the same deadline as the regular papers. The conference where the paper was published must be specified at submission. These papers will also be reviewed by the program committee. If accepted, they will be presented at the conference but will not appear in the proceedings.


Key dates:
- Joint Event: June 23-26, 2020. June 23 will be dedicated to workshops;
- RFIAP papers submission deadline for long papers (6-8 pages): February 19;
- RFIAP papers submission deadline for short papers (2 pages): March 27;
- Notification to authors for RFIAP papers: April 1;
- Early bird registration: May 29, 2020.




Topics of interest include all aspects of computer vision and pattern recognition including, but not limited to:


Document analysis
Video Analytics
Scene Analysis and understanding
Vision Applications and Systems
Non-supervised, weakly supervised machine learning, transfer learning, zero- or one-short learning
Representation learning
Biometrics
Data fusion
Discrete geometry
Medical, Biomedical imaging, bioinformatics
Recognition: Detection, categorization, indexing, and matching
Multimodal interaction
Optimization methods
Mathematical modeling for pattern recognition and perception
Image registration
Face, gesture, and action recognition
3D reconstruction
Segmentation
Motion and tracking
Vision + Language
Robotics and driving, SLAM, interaction with robots
Image-based synthesis