Search Results for author: Aladine Chetouani

Found 10 papers, 4 papers with code

A domain adaptive deep learning solution for scanpath prediction of paintings

no code implementations22 Sep 2022 Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani, Alessandro Bruno

Cultural heritage understanding and preservation is an important issue for society as it represents a fundamental aspect of its identity.

Scanpath prediction

SalyPath360: Saliency and Scanpath Prediction Framework for Omnidirectional Images

no code implementations1 Jan 2022 Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani, Mohamed Sayeh

The key setup of our architecture is the simultaneous prediction of the saliency map and a corresponding scanpath for a given stimulus.

Scanpath prediction

A Simple and efficient deep Scanpath Prediction

no code implementations8 Dec 2021 Mohamed Amine Kerkouri, Aladine Chetouani

Visual scanpath is the sequence of fixation points that the human gaze travels while observing an image, and its prediction helps in modeling the visual attention of an image.

Scanpath prediction

Learnable Triangulation for Deep Learning-based 3D Reconstruction of Objects of Arbitrary Topology from Single RGB Images

no code implementations24 Sep 2021 Tarek Ben Charrada, Hedi Tabia, Aladine Chetouani, Hamid Laga

It is composed of of (1) a Vertex Generation Network (VGN), which predicts the initial 3D locations of the object's vertices from an input RGB image, (2) a differentiable triangulation layer, which learns in a non-supervised manner, using a novel reinforcement learning algorithm, the best triangulation of the object's vertices, and finally, (3) a hierarchical mesh refinement network that uses graph convolutions to refine the initial mesh.

3D Object Reconstruction 3D Reconstruction +1

A deep perceptual metric for 3D point clouds

1 code implementation25 Feb 2021 Maurice Quach, Aladine Chetouani, Giuseppe Valenzise, Frederic Dufaux

In addition, we propose a novel truncated distance field voxel grid representation and find that it leads to sparser latent spaces and loss functions that are more correlated with perceived visual quality compared to a binary representation.

Kernelized dense layers for facial expression recognition

no code implementations22 Sep 2020 M. Amine Mahmoudi, Aladine Chetouani, Fatma Boufera, Hedi Tabia

Fully connected layer is an essential component of Convolutional Neural Networks (CNNs), which demonstrates its efficiency in computer vision tasks.

Facial Expression Recognition

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