Connectionists: Call for papers: 2nd 3D Face Alignment in the Wild Challenge & Workshop @ ICCV 2019

[Laszlo A. Jeni]

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2nd 3D Face Alignment in the Wild Challenge & Workshop
In conjunction with ICCV 2019, Seoul, Korea (Oct 27th- Nov 2nd, 2019)
Website: https://3dfaw.github.io
CMT is open: https://cmt3.research.microsoft.com/3DFAW2019
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CALL FOR PAPERS
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Over the past few years a number of research groups have made rapid
advances in dense 3D alignment from 2D images and obtained impressive
results. How these various methods compare is relatively unknown. Previous
benchmarks addressed sparse 3D alignment and single image 3D
reconstruction. No commonly accepted evaluation protocol exists for dense
3D face reconstruction from video with which to compare them.
To enable comparisons among alternative methods, we present the 2nd 3D Face
Alignment in the Wild - Dense Reconstruction from Video Challenge. This
topic is germane to both computer vision and multimedia communities. For
computer vision, it is an exciting approach to longstanding limitations of
single-image 3D reconstruction approaches. For multimedia, 3D alignment
would enable more powerful applications.


Workshop track
~~~~~~~~~~~~~~
The workshop track is intended to bring together computer vision
researchers whose work is related to 2D or 3D face alignment. We are
soliciting original contributions which address a wide range of theoretical
and application issues of 3D face alignment for computer vision
applications, including but not limited to:

- 3D face alignment from 2D dimensional images
- Model- and stereo-based 3D face reconstruction
- Dense and sparse face tracking from 2D and 3D dimensional inputs
- Applications in AR / VR
- Face alignment for embedded and mobile devices
- Facial expression retargeting (avatar animation)
- Face alignment-based user interfaces


Challenge Track
~~~~~~~~~~~~~~~
The challenge track evaluates 3D face reconstruction methods on a new large
corpora of profile-to-profile face videos annotated with corresponding
high-resolution 3D ground truth meshes. The corpora includes
profile-to-profile videos obtained under a range of conditions:

- high-definition in-the-lab video, and
- unconstrained video from an iPhone device.

For each subject, high-resolution 3D ground truth scans were obtained using
a Di4D imaging system. The goal of the challenge is to reconstruct the 3D
structure of the face from the two different video sources.


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SUBMISSION
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For paper submission, please use the CMT site:
https://cmt3.research.microsoft.com/3DFAW2019

For participating in the challenge, please visit the CodaLab page for more
details:
https://codalab.lri.fr/competitions/572
https://3dfaw.github.io

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IMPORTANT DATES
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Challenge Track
June 27th: Challenge site opens
August 1st: Testing phase begins
August 15: Competition ends

Workshop Track
July 31st: Paper submission deadline
August 21st: Notification of acceptance
August 28th: Camera ready submission


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WORKSHOP ORGANIZERS
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Laszlo A. Jeni, Carnegie Mellon University, USA
Jeffrey F. Cohn, University of Pittsburgh, USA
Lijun Yin, Binghamton University, USA

Data chairs:
Rohith Krishnan Pillai, Carnegie Mellon University, USA
Huiyuan Yang, Binghamton University, USA
Zheng Zhang, Binghamton University, USA

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TECHNICAL PROGRAM COMMITTEE
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Abhinav Dhall, Australian National University, Australia
Gábor Szirtes, KÜRT Akadémia / bsi.ai
Hamdi Dibeklioglu, Bilkent University, Turkey
Michel Valstar, University of Nottingham, UK
Patrik Huber, University of Surrey, UK
Sergio Escalera, University of Barcelona, Spain
Shaun Canavan, University of South Florida, USA
Vitomir Štruc, University of Ljubljana, Slovenia
Xiaoming Liu, Michigan State University, USA
Xing Zhang, A9
Zoltan Kato, University of Szeged, Hungary

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JOURNAL SPECIAL ISSUE
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A special issue on a top journal is planned.

For more information: https://3dfaw.github.io


-- 
+------------------------------------------
| Laszlo A. Jeni, PhD
|   Systems Scientist (faculty)
|   Robotics Institute
|   Carnegie Mellon University,
| Web: http://www.laszlojeni.com
| Email: laszlojeni at cmu.edu
| Tel:   (+1) 412-268-4461
+------------------------------------------
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