Eyes on People: Recent Trends on Human Analysis, Perception and Generation Call for Papers

Call for Papers

Eyes on People: Recent Trends on Human Analysis, Perception and Generation

Computer Vision and Image Understanding


https://www.sciencedirect.com/journal/computer-vision-and-image-understanding/about/call-for-papers#eyes-on-people-recent-trends-on-human-analysis-perception-and-generation

 

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Timeline:

Final Manuscript Submission Deadline
21/03/2024

Editorial Acceptance Deadline
21/06/2024

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Apologies for multiple posting

Please distribute this call to interested parties


AIMS AND SCOPE

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Human-centered data are extremely widespread and have been intensely
investigated by researchers belonging to very different fields. These
research efforts are motivated by the several highly-informative
aspects of humans that can be investigated, ranging from corporal
elements to emotions and outward appearance. Recent advancements in
machine and deep learning opened the way to the practical
implementation of methods that can effectively blend into the real
world, becoming for all intents and purposes an integral part of our
everyday lives. The span of possible applications is vast, ranging
from security and prevention of crimes to healthcare, social behavior,
and even entertainment.

On the other hand, the extreme variety and diffusion of human-centered
data, and the unprecedented level of accuracy of learning methods make
their analysis and use extremely challenging and critical, as it
normally involves personal and sensitive information. The improper use
of such human-centered technology can have unpredictable social
consequences if not properly taken into account. Indeed, the
collection and use of human-centered data to build AI models capable
of analyzing and predicting human behaviors raise non-negligible
concerns related to privacy, ethics, and fairness.

To conclude, we believe research efforts should go in a direction
where learning models meet the always stricter privacy and ethics
requirements. Overall, the goal of this Special Issue is to gather
research efforts in the field of human analysis, perception, and
generation. We aim at improving the communication between researchers
and companies, and developing novel ideas that can shape the future of
this area, in terms of motivations, methodologies, prospective trends,
ethics, and potential industrial applications.

TOPICS

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We encourage submissions from all areas of computer vision, machine
learning and deep learning, focusing on the analysis of humans. More
general contributions such as novel theories, frameworks,
architectures, and datasets are also welcome. The topics of interest
include, but are not limited to, the following:

Human Analysis

    Action and gesture recognition

    Behavior understanding

    Facial expression and emotion recognition

    Trajectory prediction

    Social interaction

    Interpersonal relation recognition


Human Perception

    People detection and tracking

    Person re-identification

    Person attribute classification

    2D/3D human pose estimation

    Anthropometric measurement estimation

    Facial landmark detection

    Head pose estimation

    3D body reconstruction

Human Generation

     DeepFake generation and detection

    Morphing attack generation and detection

    Virtual avatar generation

    Virtual-try On

Human-Centered Data

    Novel datasets with human data

    Fairness and biases in human analysis

    Privacy preservation and data anonymization



GUEST EDITORS

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Guido Borghi, PhD University of Bologna, Bologna, Italy

Andrea Pilzer, PhD NVIDIA, Italy

Mohamed Daoudi, PhD IMT Nord Europe, France

Xavier Alameda Pineda, PhD INRIA Grenoble, France

Federico Becattini, PhD University of Siena, Siena, Italy

Marcella Cornia, PhD University of Modena and Reggio Emilia, Modena, Italy

Claudio Ferrari, PhD University of Parma, Parma, Italy

Tomaso Fontanini, PhD University of Parma, Parma, Italy