Publications (9)
Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI
Mathieu Dubois, Fouad Hadj-Selem, Tommy Lofstedt +4
The use of machine-learning in neuroimaging offers new perspectives in early diagnosis and prognosis of brain diseases. Although such multivariate methods can capture complex relat…
Learning Long-Term Style-Preserving Blind Video Temporal Consistency
Hugo Thimonier, Julien Despois, Robin Kips +1
When trying to independently apply image-trained algorithms to successive frames in videos, noxious flickering tends to appear. State-of-the-art post-processing techniques that aim…
AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs
Julien Despois, Frederic Flament, Matthieu Perrot
Existing approaches and datasets for face aging produce results skewed towards the mean, with individual variations and expression wrinkles often invisible or overlooked in favor o…
CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer
Robin Kips, Pietro Gori, Matthieu Perrot +1
While existing makeup style transfer models perform an image synthesis whose results cannot be explicitly controlled, the ability to modify makeup color continuously is a desirable…
Hair Color Digitization through Imaging and Deep Inverse Graphics
Robin Kips, Panagiotis-Alexandros Bokaris, Matthieu Perrot +2
Hair appearance is a complex phenomenon due to hair geometry and how the light bounces on different hair fibers. For this reason, reproducing a specific hair color in a rendering e…
Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example
Robin Kips, Ruowei Jiang, Sileye Ba +5
While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task. I…
Scikit-learn: Machine Learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort +16
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses…
Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection
Hadrien Bertrand, Matthieu Perrot, Roberto Ardon +1
The classification of MRI images according to the anatomical field of view is a necessary task to solve when faced with the increasing quantity of medical images. In parallel, adva…
Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers
Robin Kips, Ruowei Jiang, Sileye Ba +4
Augmented reality applications have rapidly spread across online platforms, allowing consumers to virtually try-on a variety of products, such as makeup, hair dying, or shoes. Howe…