25 citations · 80 across the 11 of their papers we have counts for
13 papers
On the De-duplication of LAION-2B
Ryan Webster, Julien Rabin, Loic Simon +1
Generative models, such as DALL-E, Midjourney, and Stable Diffusion, have societal implications that extend beyond the field of computer science. These models require large image d…
This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces
Ryan Webster, Julien Rabin, Loic Simon +1
Recently, generative adversarial networks (GANs) have achieved stunning realism, fooling even human observers. Indeed, the popular tongue-in-cheek website {\small \url{ http://this…
Variational models for signal processing with Graph Neural Networks
Amitoz Azad, Julien Rabin, Abderrahim Elmoataz
This paper is devoted to signal processing on point-clouds by means of neural networks. Nowadays, state-of-the-art in image processing and computer vision is mostly based on traini…
On the Existence of Optimal Transport Gradient for Learning Generative Models
Antoine Houdard, Arthur Leclaire, Nicolas Papadakis +1
The use of optimal transport cost for learning generative models has become popular with Wasserstein Generative Adversarial Networks (WGAN). Training of WGAN relies on a theoretica…
A Generative Model for Texture Synthesis based on Optimal Transport between Feature Distributions
Antoine Houdard, Arthur Leclaire, Nicolas Papadakis +1
We propose GOTEX, a general framework for texture synthesis by optimization that constrains the statistical distribution of local features. While our model encompasses several exis…
On the Theoretical Equivalence of Several Trade-Off Curves Assessing Statistical Proximity
Rodrigue Siry, Ryan Webster, Loic Simon +1
The recent advent of powerful generative models has triggered the renewed development of quantitative measures to assess the proximity of two probability distributions. As the scal…
On Demand Solid Texture Synthesis Using Deep 3D Networks
Jorge Gutierrez, Julien Rabin, Bruno Galerne +1
This paper describes a novel approach for on demand volumetric texture synthesis based on a deep learning framework that allows for the generation of high quality 3D data at intera…
Revisiting Precision and Recall Definition for Generative Model Evaluation
Loïc Simon, Ryan Webster, Julien Rabin
In this article we revisit the definition of Precision-Recall (PR) curves for generative models proposed by Sajjadi et al. (arXiv:1806.00035). Rather than providing a scalar for ge…
Detecting Overfitting of Deep Generative Networks via Latent Recovery
Ryan Webster, Julien Rabin, Loic Simon +1
State of the art deep generative networks are capable of producing images with such incredible realism that they can be suspected of memorizing training images. It is why it is not…
Automatic discovery of discriminative parts as a quadratic assignment problem
Ronan Sicre, Julien Rabin, Yannis Avrithis +2
Part-based image classification consists in representing categories by small sets of discriminative parts upon which a representation of the images is built. This paper addresses t…
Convex Histogram-Based Joint Image Segmentation with Regularized Optimal Transport Cost
Nicolas Papadakis, Julien Rabin
We investigate in this work a versatile convex framework for multiple image segmentation, relying on the regularized optimal mass transport theory. In this setting, several transpo…
Convex Color Image Segmentation with Optimal Transport Distances
Julien Rabin, Nicolas Papadakis
This work is about the use of regularized optimal-transport distances for convex, histogram-based image segmentation. In the considered framework, fixed exemplar histograms define…
Transportation Distances on the Circle and Applications
Julie Delon, Julien Rabin, Yann Gousseau
This paper is devoted to the study of the Monge-Kantorovich theory of optimal mass transport and its applications, in the special case of one-dimensional and circular distributions…