activity
20172021
most citedA Novel Space-Time Representation on the Positive Semidefinite Con for Facial Expression Recognition

11 citations · 25 across the 4 of their papers we have counts for

collaborators

9 papers

cs.CV20212 cited

Disentangled Face Identity Representations for joint 3D Face Recognition and Expression Neutralisation

Anis Kacem, Kseniya Cherenkova, Djamila Aouada

In this paper, we propose a new deep learning-based approach for disentangling face identity representations from expressive 3D faces. Given a 3D face, our approach not only extrac…

cs.CV20217 cited

Face-GCN: A Graph Convolutional Network for 3D Dynamic Face Identification/Recognition

Konstantinos Papadopoulos, Anis Kacem, Abdelrahman Shabayek +1

Face identification/recognition has significantly advanced over the past years. However, most of the proposed approaches rely on static RGB frames and on neutral facial expressions…

cs.CV20205 cited

SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results

Alexandre Saint, Anis Kacem, Kseniya Cherenkova +7

The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D…

cs.CV2020

3DBooSTeR: 3D Body Shape and Texture Recovery

Alexandre Saint, Anis Kacem, Kseniya Cherenkova +1

We propose 3DBooSTeR, a novel method to recover a textured 3D body mesh from a textured partial 3D scan. With the advent of virtual and augmented reality, there is a demand for cre…

cs.CV2019

Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets

Naima Otberdout, Mohamed Daoudi, Anis Kacem +2

In this work, we propose a novel approach for generating videos of the six basic facial expressions given a neutral face image. We propose to exploit the face geometry by modeling…

cs.CV2018

Automatic Analysis of Facial Expressions Based on Deep Covariance Trajectories

Naima Otberdout, Anis Kacem, Mohamed Daoudi +2

In this paper, we propose a new approach for facial expression recognition using deep covariance descriptors. The solution is based on the idea of encoding local and global Deep Co…