Fabien Baradel

I am a first year PhD Candidate at INSA Lyon - LIRIS.
I am working on Machine Learning and Computer Vision.
My supervisors are Christian Wolf and Julien Mille.
My PhD focuses on video understanding.

My PhD thesis title:
"Deep Learning for Human Understanding: poses, gestures, activities"
funded by the ANR/NSREC DeepVision project.

I received my Engineer's degree (MSc) from ENSAI with a major in Big Data - Data Science. Previously I've been intern at Xerox Research Centre Europe.

Email  /  CV  /  Github  /  LinkedIn  /  Twitter


My main researchs focus on video understanding and specially understanding human activities. I am interested in machine learning, deep learning, computer vision and domain adaptation. I am also interested about theoritical aspects in machine learning.


Human Action Recognition: Pose-based Attention draws focus to Hands
Fabien Baradel, Christian Wolf, Julien Mille
ICCV Workshop "Hands in Action", 2017

A new spatio-temporal attention based mechanism for human action recognition able to automatically attend to most important human hands and detect the most discriminative moments in an action.


Discrepancy-based networks for unsupervised domain adaptation: a comparative study
Gabriela Csurka, Fabien Baradel, Boris Chidlovskii, Stephane Clinchant,
ICCV Workshop "Task-CV", 2017

We introduce a new dataset for Domain Adaptation and show a comparaison between shallow and deep methods based on Maximum Mean Discrepancy.


Pose-conditioned Spatio-Temporal Attention for Human Action Recognition
Fabien Baradel, Christian Wolf, Julien Mille
arXiv Preprint, 2017
arXiv / project page / video / bibtex

We introduce an attention-based mechanism around hands on RGB videos conditioned on features extracted from human 3D pose. We show state-of-the-art perfomance on the largest dataset and apply transfer learning on smaller datasets.


Regression Modelling
Univ Lyon 1 - M2 Data Science - 12h (TP) - Fall 2017

Probability & Statistics
Univ Lyon 1 - L2 Info & Maths-Eco - 12h+16h (TP) - Fall 2017

EPITA - 1st year - 24h (CM+TD) - September 2017

Introduction to Deep Learning with Tensorflow
ENSAI - MSc Data Science - 6h - January 2017
Github repo / slides

Awesome webpage...