The
FOX team from the CRIStAL laboratory (UMR CNRS), Lille France is
looking to recruit a PhD student starting on October 1st
2022 on the following subject : Spatio-temporal
data augmentation models for motion pattern learning using
deep learning: applications to facial analysis in the wild
The
FOX research group is part of the CRIStAL laboratory (University
of Lille, CNRS), located in Lille, France. We focus on video
analysis for human behavior understanding. Specifically, we
develop spatio-temporal models of motions for tasks such as
abnormal event detection, emotion recognition, and face
alignment. Our work is published in major journals (Pattern
Recognition, IEEE Trans. on Affective Computing) and conferences
(WACV, IJCNN).
Abstract:
Facial expression analysis is a well-studied field when dealing
with segmented and constrained data captured in lab conditions.
However, many challenges must still be addressed for building
in-the-wild solutions that account for various motion
intensities, strong head movements during expressions, the
spotting of the subsequence containing the expression, partially
occluded faces, etc. In recent years, learned features based on
deep learning architectures were proposed in order to deal with
these challenges. Deep learning is characterized by neural
architectures that depend on a huge number of parameters. The
convergence of these neural networks and the estimation of
optimal parameters require large amounts of training data,
especially when dealing with spatio-temporal data, particulary
adequate for facial expression recognition. The quantity, but
also the quality, of the data and its capacity to reflect the
addressed challenges are key elements for training properly the
networks. Augmenting the data artificially in an intelligent and
controlled way is an interesting solution. The augmentation
techniques identified in the literature are mainly focused on
image augmentation and consist of scaling, rotation, and
flipping operations, or they make use of more complex
adversarial training. These techniques can be applied at the
frame level, but there is a need for sequence level augmentation
in order to better control the augmentation process and ensure
the absence of temporal artifacts that might bias the learning
process. The generation of dynamic frontal facial expressions
has already been addressed in the literature. The goal of this
Ph.D. is to conceive new space-time augmentation methods for
unconstrained facial analysis (involving head movements,
occultations, etc.). Attention should be paid in assessing the
quality standards related to facial expression requirements:
stability over time, absence of facial artifacts, etc. More
specifically, the Ph.D. can
didate
is expected to conceive augmentation architectures that address
various challenges (motion intensities, head movements) while
maintaining temporal stability and eliminating facial artifacts.
Candidates
must hold a Master degree in Computer Science, Statistics,
Applied Mathematics or a related field. Experience in one or
more of the following is a plus:
•
image processing, computer vision;
•
machine learning;
•
research methodology (literature review, experimentation…).
Candidates
should have the following skills:
•
good proficiency in English, both spoken and written;
•
scientific writing;
•
programming (experience in C++ is a plus, but not mandatory).
This
PHD thesis will be funded in the framework of the AI_PhD@Lilleprogram.
The
candidate will be funded for 3 years; he/she is expected to
defend his/her thesis and graduate by the end of the contract.
The monthly gross salary is around 2000€, including benefits
(health insurance, retirement fund, and paid vacations).
Additional financial support is expected in the framework of the
AI_PhD@Lille
program.
The
position is located in Lille,
France.
With over 110 000 students, the metropolitan area of Lille is
one France's top education student cities. The European Doctoral
College Lille Nord-Pas de Calais is headquartered in Lille
Metropole and includes 3,000 PhD Doctorate students supported by
university research laboratories. Lille has a convenient
location in the European high-speed rail network. It lies on the
Eurostar line to London (1:20 hour journey). The French TGV
network also puts it only 1 hour from Paris, 35 mn from
Brussels, and a short trips to other major centres in France
such as Paris, Marseille and Lyon.
We
look forward to receiving your application
as soon as possible,
but no later than 26.03.2021.