[visionlist] Adaptive Shot Learning for Gesture Understanding and Production (in conjunction with IEEE FG 2017) – CFP

Apologies for multiple copies



1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production

ASL4GUP 2017

In conjunction with IEEE FG 2017

May 30, 2017, Washington DC, USA


Contact: jpwachs@purdue.edu




Submission Deadline: Feb 1, 2017

Notification of Acceptance: March 1, 2017

Camera Ready: March 8, 2017

Workshop: May 30, 2017




In the aim of natural interaction with machines, a framework must be developed to include the adaptability humans portray to understand gestures from context, from a single observation or from multiple observations. This is also referred as adaptive shot learning Ð the ability to adapt the mechanism of recognition to a barely seen gesture, well-known or entirely unknown. Of particular interest to the community are zero-shot and one-shot learning, given that most work has been done in the N-shot learning scenario. The workshop aims to encourage works that focus on the way in which humans produce gestures Ð the kinematic and biomechanical characteristics, and the cognitive process involved when perceiving, remembering and replicating them. We invite submission of papers presenting original research in the aforementioned theme.




Topics of interest (but not limited to):

* One and zero shot recognition;

* Gesture production from context or single observation;

* EEG based gesture recognition

* Context modeling from gesture languages;

* Holistic approaches to gesture modeling and recognition;

* Human-like gesture production and recognition;

* Gesture based robotic control and interfaces




Submissions may be up to 8 pages, in accordance with the IEEE FG conference format. Papers longer than six pages will be subject to a page fee (100 USD per page) for the extra pages (two max). We welcome regular, position and applications papers.  Submission through:


Accepted papers will be included in the Proceedings of IEEE FG 2017 & Workshops and will be sent for inclusion into the IEEE Xplore digital library. Selected papers will be also invited for a full submission to a special issue in a leading journal in the field of machine learning and cognition.




Juan P Wachs (Purdue University, USA); jpwachs@purdue.edu

Richard Voyles (Purdue University, USA); rvoyles@purdue.edu

Susan Fussell (Cornell University, USA); sfussell@cornell.edu

Isabelle Guyon (UniversitŽ Paris-Saclay, France); guyon@clopinet.com

Sergio Escalera (Computer Vision Center and University of Barcelona, Spain); sergio.escalera.guerrero@gmail.com


Program Committee


1. Nadia Bianchi-Berthouze, University College London, UK (confirmed)

2. Albert Ali Salah, Bogazici University, Turkey  (confirmed)

3. Adar Pelah, University of York, UK   (confirmed)

4. Hugo Jair Escalante, INAOE, Mexico   (confirmed)

5. Jun Wan, Insitute of Automation, Chinese Academy of Sciences, China (confirmed)

6. Miriam Zacksenhouse, Technion, Israel (confirmed)

7. Marta Mejail, Universidad de Buenos Aires (UBA), Argentina (confirmed)

8. Tamar Flash, The Weizmann Institute of Science, Israel (confirmed)

9. Luigi Gallo, Institutes of the National Research Council, Italy (confirmed)

10. Mathew Turk, University of California, Santa Barbara, USA (confirmed)

11. Daniel Gill, University of Winchester (UK) (confirmed)

12. Ray Perez, Office of Naval Research (ONR) – USA (confirmed)

13. Daniel Foti (Purdue) – USA (confirmed)

14. Yael Edan (Ben-Gurion University of the Negev) – Israel (confirmed).


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