Search Results for author: Matthieu Perrot

Found 7 papers, 1 papers with code

Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

no code implementations12 May 2021 Robin Kips, Ruowei Jiang, Sileye Ba, Edmund Phung, Parham Aarabi, Pietro Gori, Matthieu Perrot, Isabelle Bloch

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.

Virtual Try-on

Learning Long-Term Style-Preserving Blind Video Temporal Consistency

no code implementations12 Mar 2021 Hugo Thimonier, Julien Despois, Robin Kips, Matthieu Perrot

When trying to independently apply image-trained algorithms to successive frames in videos, noxious flickering tends to appear.

Image Manipulation Style Transfer +1

AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs

no code implementations25 Aug 2020 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 of global patterns such as the fattening of the face.

CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer

no code implementations24 Aug 2020 Robin Kips, Pietro Gori, Matthieu Perrot, Isabelle Bloch

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 property for virtual try-on applications.

Image Generation Style Transfer +1

Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection

no code implementations16 Jan 2017 Hadrien Bertrand, Matthieu Perrot, Roberto Ardon, Isabelle Bloch

Improving the model is not an easy task, due to the large number of hyper-parameters governing both the architecture and the training of the network, and to the limited understanding of their relevance.

Gaussian Processes General Classification +1

Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI

no code implementations21 Jul 2014 Mathieu Dubois, Fouad Hadj-Selem, Tommy Lofstedt, Matthieu Perrot, Clara Fischer, Vincent Frouin, Edouard Duchesnay

This algorithm uses Nesterov's smoothing technique to approximate the TV penalty with a smooth function such that the loss and the penalties are minimized with an exact accelerated proximal gradient algorithm.

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