[visionlist] ICCV Workshop on Human Behavior Understanding (HBU): Generating, Forging and Detecting Fake Human Behavioral Data

[Elisa Ricci]

10th Workshop on Human Behavior Understanding (HBU)
In conjunction with International Conference on Computer Vision (ICCV) 2019
27 October 2019, Seoul, Korea

Focus Theme: *Generating, Forging and Detecting Fake Human Behavioral Data*
https://project.inria.fr/whbu/

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CALL FOR PAPERS

As in many other computer vision tasks, deep learning has brought
revolutionary advances in human behaviour understanding from visual data.
Deep models are now extremely effective  not only in detecting and
analyzing human faces, bodies and collective activities but also in
generating realistic human-like behavioral data. From full-body deepfakes
to AI-based translation dubbing, deep networks can now synthesize images
and videos of humans such as they are virtually indistinguishable from real
ones. The workshop will focus on recent advances and novel methodologies
for generating human behaviour data, with special emphasis on approaches
for forging images and videos depicting real-looking human faces and/or
full bodies and on algorithms for detecting fake human-like visual data.

The HBU workshops, organized since 2010 as satellite to ICPR’10, AMI’11,
IROS’12, ACM Multimedia’13, ECCV’14 and UBICOMP’15, ACM Multimedia’16,
FG’18, ECCV’18 Conferences, aim to inspect developments in areas where
smarter computers that can sense human behavior. These events have a unique
aspect of fostering cross-pollination of different disciplines, bringing
together researchers of mobile and ubiquitous computing, computer vision,
multimedia, robotics, HCI, artificial intelligence, pattern recognition,
interaction design, ambient intelligence, and psychology. The diversity of
human behavior, the richness of multi-modal data that arises from its
analysis, and the multitude of applications that demand rapid progress in
this area ensure that the HBU Workshops provide a timely and relevant
discussion and dissemination platform.

Each edition of the HBU workshop had a different focus theme, dealing with
a newly emerging topic or question in the automatic analysis of human
behavior. The focus theme of this year is of high interest for computer
vision researchers: *Generating, Forging and Detecting Fake Human
Behavioral Data*. The automatic generation of visual contents is currently
a very hot topic in the community. With this edition of the HBU workshops,
we attempt to foster research on how to generate visual data (still images
and videos) describing human behavior both from the applicative and
methodological points of view.



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TOPICS

ICCV’2019 HBU workshop, in addition to covering the main themes of human
behavior understanding, deals with generating human behavior data, with
special *emphasis on methodologies and approaches for forging images and
videos depicting real-looking human faces *and/or full bodies and on
algorithms for detecting fake human-like visual data. Contributions based
on deep neural architectures are welcome, as well as methods based on other
techniques (e.g. parametric models). These contributions could address the
following topics:

*Human Behavior Analysis Systems*

   -

   Action and activity recognition
   -

   Affect analysis
   -

   Face analysis
   -

   Gaze, attention and saliency
   -

   Gestures and haptic interaction
   -

   Social signal processing
   -

   Voice and speech analysis
   -

   Theoretical frameworks of behavior analysis
   -

   Data collection, annotation, and benchmarking
   -

   User studies and human factors

*Generating Visual data of Human Behavior*

   -

   Methods for face synthesis and modification of facial attributes (e.g.
   age, expression).
   -

   Approaches for generating human bodies and altering their properties
   (e.g. 3D pose, clothes).
   -

   Techniques for forging human-like behavioral data
   -

   Methodologies for counteracting adversarial attacks.
   -

   Techniques for synthesizing visual data depicting collective human
   behaviour.
   -

   Novel deep generative models for sequence-like data generation.
   -

   Approaches to synthesize multi-modal human behavioral data.
   -

   Applications (e.g. surveillance, entertainment, autonomous driving,
   fashion, robotics).



Papers must be submitted online through the CMT submission system at:
https://easychair.org/conferences/?conf=hbu2019
and will be double-blind peer reviewed by at least two reviewers.
Submissions should conform to the ICCV 2019 proceedings style.

We expect two kind of submissions:

   -

   Full papers of new contributions (8 pages NOT including references)
   -

   Short papers describing incremental/preliminary work (2 pages NOT
   including references)


More info at: https://project.inria.fr/whbu/

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IMPORTANT DATES
Regular Paper Submission: *July 1st, 2019*
Extended Abstract Submission: *July 15th, 2019*
Notification of Acceptance: *July 31st, 2019*
Camera-Ready: *August 15th, 2019*

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INVITED SPEAKERS

*Cristian Sminchisescu*, Google & Lund University, DE
*Hao Li*, University of Southern California, USA


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ORGANIZERS:
Xavier Alameda-Pineda, Inria, FR.
Xiaoming Liu, Michigan State University, USA.
Elisa Ricci, FBK & University of Trento, IT.
Albert Ali Salah, Boğaziçi University, TR & Utrecht University, NL.
Nicu Sebe, University of Trento, IT.
Sergey Tulyakov, Snap Research, USA.

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