Search Results for author: Lara Raad

Found 7 papers, 1 papers with code

Scaling Painting Style Transfer

no code implementations27 Dec 2022 Bruno Galerne, Lara Raad, José Lezama, Jean-Michel Morel

Neural style transfer is a deep learning technique that produces an unprecedentedly rich style transfer from a style image to a content image and is particularly impressive when it comes to transferring style from a painting to an image.

Style Transfer

Photorealistic Facial Wrinkles Removal

no code implementations3 Nov 2022 Marcelo Sanchez, Gil Triginer, Coloma Ballester, Lara Raad, Eduard Ramon

In this work, we revisit a two-stage approach for retouching facial wrinkles and obtain results with unprecedented realism.

Analysis of Different Losses for Deep Learning Image Colorization

no code implementations6 Apr 2022 Coloma Ballester, Aurélie Bugeau, Hernan Carrillo, Michaël Clément, Rémi Giraud, Lara Raad, Patricia Vitoria

While learning to automatically colorize an image, one can define well-suited objective functions related to the desired color output.

Colorization Image Colorization

Influence of Color Spaces for Deep Learning Image Colorization

no code implementations6 Apr 2022 Coloma Ballester, Aurélie Bugeau, Hernan Carrillo, Michaël Clément, Rémi Giraud, Lara Raad, Patricia Vitoria

In this chapter, we aim to study their influence on the results obtained by training a deep neural network, to answer the question: "Is it crucial to correctly choose the right color space in deep-learning based colorization?".

Colorization Image Colorization

ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution

3 code implementations23 Jul 2019 Patricia Vitoria, Lara Raad, Coloma Ballester

In this paper, we propose an adversarial learning colorization approach coupled with semantic information.

Colorization

A survey of exemplar-based texture synthesis

no code implementations22 Jul 2017 Lara Raad, Axel Davy, Agnès Desolneux, Jean-Michel Morel

The two main approaches are statistics-based methods and patch re-arrangement methods.

Texture Synthesis

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