activity
20082022
most citedCA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer

30 citations · 116 across the 24 of their papers we have counts for

collaborators

27 papers

eess.SP2022

Morphological adjunctions represented by matrices in max-plus algebra for signal and image processing

Samy Blusseau, Santiago Velasco-Forero, Jesus Angulo +1

In discrete signal and image processing, many dilations and erosions can be written as the max-plus and min-plus product of a matrix on a vector. Previous studies considered operat…

cs.CV2021

Automatic size and pose homogenization with spatial transformer network to improve and accelerate pediatric segmentation

Giammarco La Barbera, Pietro Gori, Haithem Boussaid +6

Due to a high heterogeneity in pose and size and to a limited number of available data, segmentation of pediatric images is challenging for deep learning methods. In this work, we…

stat.ML2021

Template-Based Graph Clustering

Mateus Riva, Florian Yger, Pietro Gori +2

We propose a novel graph clustering method guided by additional information on the underlying structure of the clusters (or communities). The problem is formulated as the matching…

cs.CV2021

Knowledge distillation from multi-modal to mono-modal segmentation networks

Minhao Hu, Matthis Maillard, Ya Zhang +4

The joint use of multiple imaging modalities for medical image segmentation has been widely studied in recent years. The fusion of information from different modalities has demonst…

cs.CV2021★ 1 cited

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…

cs.CV2021★ 1 cited

Approximation of dilation-based spatial relations to add structural constraints in neural networks

Mateus Riva, Pietro Gori, Florian Yger +2

Spatial relations between objects in an image have proved useful for structural object recognition. Structural constraints can act as regularization in neural network training, imp…